[{"data":1,"prerenderedAt":2198},["ShallowReactive",2],{"category-artificial-intelligence":3},{"category":4,"posts":52,"featured":1959,"ebooks":2089},{"id":5,"count":6,"description":7,"link":8,"name":9,"slug":10,"taxonomy":11,"parent":12,"meta":13,"acf":14,"z_taxonomy_image_url":27,"yoast_meta":28,"taxonomy_image":27,"_links":31},504,228,"\u003Cspan data-sheets-value=\"{\" data-sheets-userformat=\"{\">\u003Cstrong>Artificial intelligence\u003C\u002Fstrong> has unimaginable potential. Within the next couple of years, it will revolutionize every area of our life, including medicine.\u003C\u002Fspan>\r\n\r\nArtificial intelligence moved from being a futuristic promise into a reference point for innovation. The technology also started to transform medicine with great vigor. In the last couple of years, the number of A.I.-related studies, research projects, university courses, and companies has grown exponentially, not to speak about the rapid improvement in the precision of the technology.\r\n\r\nAt The Medical Futurist, we are sure that Artificial Intelligence is not going to replace medical professionals; it’s going to be the stethoscope of the 21st century and successful collaboration between humans and technology could bring us the positive change in medicine that we all so strongly wish for.\r\n\r\nDigital health will give us more health data than ever before, and A.I will help us analyze it to find new ways to treat diseases, to cut down on administrative tasks, to streamline medical practices, to optimize both physicians’ and patients’ schedules.","https:\u002F\u002Fapi.medicalfuturist.com\u002Fcategory\u002Fartificial-intelligence\u002F","Artificial Intelligence in Medicine","artificial-intelligence","category",0,[],{"listing_order":15,"child_category_ids":16,"featured":17,"youtube_video_id":22,"sub_header":23,"excerpt":24,"ebooks":25},"1",false,[18,19,20,21],24083,14848,13650,15909,"Ec7Wu2JMvPw","What You Have To Know About Artificial Intelligence in Medicine?","\u003Cp>Artificial intelligence algorithms are not only making our cars safer and shopping easier, but increasingly diagnose patients and help make the best decisions when caring for them. Learn more about Artificial Intelligence in Medicine.\u003C\u002Fp>\n",[26],24762,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Fradiologist_001-1.png",{"yoast_wpseo_title":29,"yoast_wpseo_metadesc":30},"Artificial Intelligence In Medicine: Examples - The Medical Futurist","Examples of Artificial Intelligence In Medicine: 1) An AI algorithm, for example, can provide a reliable map of future virus outbreak hot spots.",{"self":32,"collection":38,"about":41,"wp:post_type":44,"curies":47},[33],{"href":34,"targetHints":35},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories\u002F504",{"allow":36},[37],"GET",[39],{"href":40},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories",[42],{"href":43},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftaxonomies\u002Fcategory",[45],{"href":46},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts?categories=504",[48],{"name":49,"href":50,"templated":51},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",true,[53,230,330,507,613,728,841,929,1054,1174,1295,1423,1530,1634,1744,1857],{"id":54,"date":55,"date_gmt":56,"guid":57,"modified":59,"modified_gmt":60,"slug":61,"status":62,"type":63,"link":64,"title":65,"content":67,"excerpt":69,"author":71,"featured_media":72,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":76,"categories":77,"tags":82,"project_category":91,"contact_email_category":94,"yst_prominent_words":95,"class_list":101,"better_featured_image":123,"acf":165,"yoast_meta":179,"_links":181},51051,"2026-07-27T15:05:43","2026-07-27T13:05:43",{"rendered":58},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=51051&_wpnonce=97a14c9231&status=auto-draft&type=post","2026-07-27T15:05:45","2026-07-27T13:05:45","health-equity-in-the-ai-and-digital-health-era-promise-or-peril","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fhealth-equity-in-the-ai-and-digital-health-era-promise-or-peril",{"rendered":66},"Health Equity In The AI And Digital Health Era: Promise Or Peril?",{"rendered":68,"protected":16},"\n\u003Cp>Will digital health and\u002For artificial intelligence improve health equity? This is one of the questions I most often get. Despite its seemingly straightforward nature, the answer isn’t a simple yes or no. As this is going to be a lengthy analysis, here is the TL;DR summary: yes, digital health and AI will eventually very likely improve health equity. But it will take time; and during this transition period, it might even temporarily widen the gap. What is important to understand is that health equity through digital health is not a technological matter. \u003C\u002Fp>\n\n\n\n\u003Cp>In the long term, the critical question we need to answer is: does the introduction of technologies into healthcare, as part of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-health\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">this cultural revolution\u003C\u002Fa>, increase or decrease people’s access to healthcare?\u003C\u002Fp>\n\n\n\n\u003Cp>Theoretically, the introduction of technology should enhance access to healthcare. It assumes repetitive tasks, expedites onboarding for patients (making it simpler and quicker for them to receive aid from the moment a problem arises), and consequently liberates human resources, which has long been the healthcare systems’ bottleneck.\u003C\u002Fp>\n\n\n\n\u003Cp>However, the caveat here is that these advantages will only be accessible to those who can access the technology. \u003Cstrong>Thus, the health equity gap is fundamentally a tech gap\u003C\u002Fstrong>. And this tech gap is in itself a wealth and an education gap. Therefore, at the end of the day, we are confronted with an enormously profound social issue.\u003C\u002Fp>\n\n\n\n\u003Cp>My team and I are working on the first part: facilitating a world where health equity issues are addressed through technology, which I believe is the most effective approach. But I\u002Fwe don’t have the means to influence the second part.\u003C\u002Fp>\n\n\n\n\u003Cp>In this \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwill-digital-health-widen-or-close-the-health-inequity-gap\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">earlier analysis of digital health equity\u003C\u002Fa>, I defined health equity as the state of affairs when everyone can attain their full potential for health and well-being. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Imagine that digital health terminates the zip-code lottery\u003C\u002Fh2>\n\n\n\n\u003Cp>Ideally, we all should live in a world where your health isn’t determined by your zip code, the amount of wealth you possess, or your level of education. Technology – specifically, digital health and artificial intelligence (AI) – is the principal architect of this equitable health utopia. Sounds fascinating, doesn’t it?\u003C\u002Fp>\n\n\n\n\u003Cp>However, transforming this vision into reality is a complex challenge. Technology’s role in healthcare can both enhance and potentially limit people’s access to healthcare services. Let’s explore this paradox further.\u003C\u002Fp>\n\n\n\n\u003Cp>While we can work diligently to enhance health equity via technology, addressing wealth and education gaps, critical prerequisites for effective technology adoption, is beyond our immediate control.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>To put it bluntly, no matter how advanced the cardiological screening features are on the latest smartwatches, they are useless if their price exceeds an individual’s \u003C\u002Fstrong>\u003Ca href=\"https:\u002F\u002Fworldpopulationreview.com\u002Fcountry-rankings\u002Fmedian-income-by-country\" target=\"_blank\" rel=\"noreferrer noopener\">\u003Cstrong>monthly or even annual wage\u003C\u002Fstrong>\u003C\u002Fa>\u003Cstrong>. The theoretical promise of an early alarm will never become a reality.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F213_tmf-01-768x432.png\" alt=\"Can your smartwatch send you to the hospital?\" class=\"wp-image-30731\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F213_tmf-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F213_tmf-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F213_tmf-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F213_tmf-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">How to relate to this challenge? \u003C\u002Fh2>\n\n\n\n\u003Cp>The complex nature of this problem becomes obvious if you try to understand how different actors think about this phenomenon and what solutions they propose. Depending on where the specific stakeholder stands, their point of view – and their suggestions will be radically different.\u003C\u002Fp>\n\n\n\n\u003Cp>For example, the consulting firm, McKinsey, \u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Findustries\u002Flife-sciences\u002Four-insights\u002Fdigital-health-an-opportunity-to-advance-health-equity\" target=\"_blank\" rel=\"noreferrer noopener\">analyses the issue from a business angle\u003C\u002Fa>, offering accurate insights and valuable tips for companies grappling with this issue. However, these insights don’t mitigate the challenges faced by those who can’t afford the technology or services.\u003C\u002Fp>\n\n\n\n\u003Cp>The World Health Organization (WHO) posits this challenge as a \u003Ca href=\"https:\u002F\u002Fwww.who.int\u002Feurope\u002Fpublications\u002Fi\u002Fitem\u002FWHO-EURO-2022-6810-46576-67595\" target=\"_blank\" rel=\"noreferrer noopener\">digital health literacy issue\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>While this is also correct, we need to take a step back as people do need the technology to use it, and if they don’t, their skill (or lack) of digital health literacy makes no difference. However, I like this conclusion from the WHO: “Yet a focus on digital approaches may inadvertently widen existing inequities in health if known inequalities in access, use and engagement with digital technology are not considered and addressed.” Also interesting is WHO’s conclusion that most studies do not take the complex nature of digital health equity into account and typically observe just one variable. \u003C\u002Fp>\n\n\n\n\u003Cp>This \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fbooks\u002FNBK580635\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">textbook chapter\u003C\u002Fa> also handles the case by focusing on the tech side – which again creates the same vacuum: we are leaving people without tech behind. \u003C\u002Fp>\n\n\n\n\u003Cp>In response, several digital health equity frameworks have been proposed, such as the one presented in \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-022-00663-0\" target=\"_blank\" rel=\"noreferrer noopener\">Nature Digital Medicine in 2022\u003C\u002Fa>. These frameworks underscore the digital determinants of health, which play a significant role in amplifying or mitigating health disparities in the digital age. For instance, an individual without a reliable internet connection or access to a device cannot benefit from the digital health revolution, regardless of how patient-centric or well-designed the healthcare application might be.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002Ftmf_article_279-01-768x432.png\" alt=\"\" class=\"wp-image-35099\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002Ftmf_article_279-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002Ftmf_article_279-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002Ftmf_article_279-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002Ftmf_article_279-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Some projects are attempting to bridge the digital divide. For example, the \u003Ca href=\"https:\u002F\u002Fwww.miragenews.com\u002Fgood-things-happening-to-support-digital-health-531756\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">digital health literacy initiative\u003C\u002Fa>, funded by the Australian Digital Health Agency, has trained and resourced 232 digital health mentors. Through their “Health My Way” program, community organizations teach digital health literacy skills, improving digital inclusion. As a result, 80% of participants reported increased digital health literacy skills and confidence.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Many lives and percentage points of GDP are at stake\u003C\u002Fh2>\n\n\n\n\u003Cp>The stakes of health inequity are high, and the socioeconomic implications are substantial. According to a report by the World Economic Forum in 2019, poor health costs the U.S. economy about $3.2 trillion per year from premature deaths and the loss of productive potential associated with diseases. \u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Fmgi\u002Foverview\u002Fin-the-news\u002Fpoor-health-reduces-global-gdp-by-15-percent-each-year\" target=\"_blank\" rel=\"noreferrer noopener\">This report estimated\u003C\u002Fa> that poor health reduces global GDP by 15% each year. \u003C\u002Fp>\n\n\n\n\u003Cp>On the flip side, equalizing healthcare access and quality has healthful effects on the economy at large. Digital technology could narrow the health equity gap by simplifying complex medical processes and removing travel barriers to healthcare access.\u003C\u002Fp>\n\n\n\n\u003Cp>Figures indicate that underrepresented and\u002For disadvantaged (poor, rural, minority, women, LGBTQ, etc) groups have significantly less access to all the cutting-edge solutions digital health offers. Thus the gap is not only not closing, but it’s rather further widening right now.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-768x432.png\" alt=\"AI bias algorithm artificial intelligence people patients race population\" class=\"wp-image-41809\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>With the right policies, incentives, subsidies and education, digital health will aid these underrepresented groups, and not just them. It could also help with problems like the “diagnostic odyssey,” a term that describes the long, often arduous journey that individuals with rare conditions undertake before they meet the right specialist. According to the National Organization for Rare Disorders, this odyssey averages five years in the United States. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">We need money, money and goodwill in policies\u003C\u002Fh2>\n\n\n\n\u003Cp>All things considered, we can conclude that, in theory, digital health and AI offer significant potential to improve health equity, even though this goes beyond being just a technological issue. These advantages might not be immediately accessible to everyone, but over time, they will become increasingly mainstream – as did many breakthrough technologies throughout the centuries from electricity through washing machines to mobile phones. \u003C\u002Fp>\n\n\n\n\u003Cp>However, it’s important to acknowledge a potential pitfall. If the main motivation of policymakers\u002Finsurance companies and other stakeholders for increased digitization of healthcare is to cut costs and withdraw resources freed up by technology adoption, we will end up in a place where access isn’t improved for anyone. The result? Technology simply becomes a tool for cost-cutting rather than an agent of change.\u003C\u002Fp>\n\n\n\n\u003Cp>So here are my takeaways: \u003C\u002Fp>\n\n\n\n\u003Col class=\"wp-block-list\">\n\u003Cli>Digital health elevates health equity, but only for those with access to technology.\u003C\u002Fli>\n\n\n\n\u003Cli>The digital health revolution itself won’t change this status quo; that’s not its mission or target audience.\u003C\u002Fli>\n\n\n\n\u003Cli>To leverage digital health to enhance health equity, we must improve digital equity – a task for policymakers and politicians.\u003C\u002Fli>\n\n\n\n\u003Cli>If we don’t redirect the human resources and capacities liberated by digital health and AI towards improving care, and instead choose to cut positions to save on operational costs, the system will ultimately see no improvements even if all previous conditions are met.\u003C\u002Fli>\n\u003C\u002Fol>\n",{"rendered":70,"protected":16},"\u003Cp>Health equity through digital health and AI is not a technological matter, but a socioeconomic one that needs to be addressed accordingly.\u003C\u002Fp>\n",6,51075,"closed","","standard",{"_acf_changed":16,"footnotes":74},[78,5,79,80,81],7079,496,489,494,[83,84,85,86,87,88,89,90],1355,134,144,207,313,6989,7815,7817,[92,93],950,952,[],[96,97,98,99,100],1617,1681,1719,4707,5323,[102,63,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122],"post-51051","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","category-artificial-intelligence","category-health-sensors-trackers","category-personalized-medicine","category-telemedicine","tag-health-literacy","tag-ai","tag-artificial-intelligence","tag-digital-health","tag-medicine","tag-digital-health-literacy","tag-health-equity","tag-digital-health-equity","project_category-medical-professionals","project_category-policy-makers",{"id":72,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":125,"post":54,"source_url":164},"image",{"width":126,"height":127,"file":128,"filesize":129,"sizes":130,"image_meta":162},1920,1080,"2023\u002F05\u002Ftmf_article_366.png",133563,{"medium":131,"large":138,"thumbnail":144,"medium_large":149,"1536x1536":150,"2048x2048":156},{"file":132,"width":133,"height":134,"mime-type":135,"filesize":136,"source_url":137},"tmf_article_366-370x208.png","370","208","image\u002Fpng","58425","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-370x208.png",{"file":139,"width":140,"height":141,"mime-type":135,"filesize":142,"source_url":143},"tmf_article_366-768x432.png","768","432","143888","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-768x432.png",{"file":145,"width":146,"height":146,"mime-type":135,"filesize":147,"source_url":148},"tmf_article_366-150x150.png","150","20824","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-150x150.png",{"file":139,"width":140,"height":141,"mime-type":135,"filesize":142,"source_url":143},{"file":151,"width":152,"height":153,"mime-type":135,"filesize":154,"source_url":155},"tmf_article_366-1536x864.png","1536","864","333798","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-1536x864.png",{"file":157,"width":158,"height":159,"mime-type":135,"filesize":160,"source_url":161},"tmf_article_366-2048x1152.png","2048","1152","472398","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},"0","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366.png",{"cta_type":166,"cta_color":74,"related_books":167,"related_posts_footer":170,"related_posts":16,"subtitle":74,"key_takeaways":174},"subscribe",[26,168,169],37033,30419,[171,172,173],50859,22987,33799,[175,177],{"title":176},"\u003Cp>Will digital health and\u002For artificial intelligence improve health equity?\u003C\u002Fp>\n",{"title":178},"\u003Cp>Yes, digital health and AI will eventually very likely improve health equity. But it will take time; and during this transition period, it might even temporarily widen the gap. What is important to understand is that health equity through digital health is not a technological matter.\u003C\u002Fp>\n",{"yoast_wpseo_title":66,"yoast_wpseo_metadesc":180,"yoast_wpseo_canonical":64},"Health equity through digital health and AI is not a technological matter, but a socioeconomic one that needs to be addressed accordingly.",{"self":182,"collection":187,"about":190,"author":193,"replies":196,"version-history":199,"predecessor-version":203,"wp:featuredmedia":207,"wp:attachment":210,"wp:term":213,"curies":228},[183],{"href":184,"targetHints":185},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51051",{"allow":186},[37],[188],{"href":189},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[191],{"href":192},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[194],{"embeddable":51,"href":195},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[197],{"embeddable":51,"href":198},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=51051",[200],{"count":201,"href":202},10,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51051\u002Frevisions",[204],{"id":205,"href":206},61019,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51051\u002Frevisions\u002F61019",[208],{"embeddable":51,"href":209},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F51075",[211],{"href":212},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=51051",[214,216,219,222,225],{"taxonomy":11,"embeddable":51,"href":215},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=51051",{"taxonomy":217,"embeddable":51,"href":218},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=51051",{"taxonomy":220,"embeddable":51,"href":221},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=51051",{"taxonomy":223,"embeddable":51,"href":224},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=51051",{"taxonomy":226,"embeddable":51,"href":227},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=51051",[229],{"name":49,"href":50,"templated":51},{"id":231,"date":232,"date_gmt":233,"guid":234,"modified":236,"modified_gmt":237,"slug":238,"status":62,"type":63,"link":239,"title":240,"content":242,"excerpt":244,"author":246,"featured_media":247,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":248,"categories":249,"tags":251,"project_category":252,"contact_email_category":253,"yst_prominent_words":254,"class_list":258,"better_featured_image":261,"acf":278,"yoast_meta":286,"_links":288},57841,"2026-07-02T06:55:25","2026-07-02T04:55:25",{"rendered":235},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=57841&_wpnonce=2169b48eca&status=auto-draft&type=post","2026-07-02T06:55:26","2026-07-02T04:55:26","drug-discovery-in-the-age-of-ai","https:\u002F\u002Fmedicalfuturist.com\u002Fdrug-discovery-in-the-age-of-ai",{"rendered":241},"Drug Discovery In The Age of AI",{"rendered":243,"protected":16},"\n\u003Cp>Previously, we contemplated the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fai-assistance-in-clinical-trials-the-practical-opportunities\" target=\"_blank\">practical opportunities\u003C\u002Fa> of the assistance of artificial intelligence (AI) technologies in clinical trials for drug development. Such assistance extends before and after trials commence, and in this article, we will focus on the pre-clinical trial aspect. \u003C\u002Fp>\n\n\n\n\u003Cp>In particular, we will focus on the drug discovery stage which involves the identification and creation of new medications. This process has, traditionally, been a \u003Ca href=\"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Ffull\u002F10.1080\u002F23808993.2024.2393089\" target=\"_blank\" rel=\"noreferrer noopener\">time-consuming and labour-intensive\u003C\u002Fa> one. In the age of AI, drug discovery can be made more efficient and precise. We will take a look at how this can be the case in this article.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The drug discovery process\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The drug discovery process can be considered as the first stage in drug development. This \u003Ca href=\"https:\u002F\u002Fmatchtrial.health\u002Fen\u002Fhow-long-does-it-take-to-develop-a-new-drug\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">usually starts with\u003C\u002Fa> the identification of a target protein that is associated with a disease. Once identified, “high-performance selection” is performed to find molecules that can bind to and influence the target. These molecules become the initial drug candidates.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002Ftmf_article_291_A-02-768x432.png\" alt=\"\" class=\"wp-image-36305\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002Ftmf_article_291_A-02-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002Ftmf_article_291_A-02-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002Ftmf_article_291_A-02-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002Ftmf_article_291_A-02.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>These candidates then need to be optimised to enhance their binding to the target. Afterwards, they are characterised to understand their actions in the human body. Following these steps, a successful molecule can proceed to further drug development stages.\u003C\u002Fp>\n\n\n\n\u003Cp>Traditionally, the drug discovery process has involved \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Ffull\u002F10.1080\u002F23808993.2024.2393089\" target=\"_blank\">considerable trial-and-error research\u003C\u002Fa> before a drug can proceed to further developmental stages. Now, AI technology can enhance the process.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>AI’s role in drug discovery\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The assistance of computers and mathematical models in designing new drugs stretches\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ft.com\u002Fcontent\u002Fb279d3d4-f1b5-4733-8e64-fcbf90d12219\" target=\"_blank\"> as far back as the 1970s\u003C\u002Fa>. However, in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcategory\u002Fartificial-intelligence\" target=\"_blank\">the current age of AI\u003C\u002Fa> that we live in, such assistance has taken a new dimension. Such smart algorithms can aid \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Ffull\u002F10.1080\u002F23808993.2024.2393089\" target=\"_blank\">virtually every step\u003C\u002Fa> in drug discovery and beyond. In the past decade alone, the amount of AI-discovered drugs has significantly increased. In 2023, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fpharmaceutical-journal.com\u002Farticle\u002Ffeature\u002Fhow-ai-is-transforming-drug-discovery\" target=\"_blank\">46 reached\u003C\u002Fa> phase II and III clinical trials. \u003C\u002Fp>\n\n\n\n\u003Cp>We dedicated an article to the \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fai-assistance-in-clinical-trials-the-practical-opportunities\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">assistance of AI in clinical trials\u003C\u002Fa>. But before reaching these stages, AI can also provide assistance. Here, we will consider the practical side of the drug discovery stage with some concrete examples.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002Ftmf_article_382-2-s-768x432.png\" alt=\"\" class=\"wp-image-52039\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002Ftmf_article_382-2-s-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002Ftmf_article_382-2-s-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002Ftmf_article_382-2-s.png 1500w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Identifying targets\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>The analytic prowess of AI models enables them to scan \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.forbes.com\u002Fcouncils\u002Fforbesbusinesscouncil\u002F2024\u002F02\u002F29\u002Fai-is-rapidly-transforming-drug-discovery\u002F\" target=\"_blank\">considerable amounts of datasets\u003C\u002Fa>, from genomic to clinical data. This, in turn, allows them to precisely identify targets and how potential drugs will interact with them, in a time-efficient manner. \u003C\u002Fp>\n\n\n\n\u003Cp>London-based \u003Ca href=\"https:\u002F\u002Fwww.benevolent.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Benevolent AI\u003C\u002Fa> leverages this ability to analyse data from the scientific literature, as well as clinical and chemical databases. Through such an approach, they could develop \u003Ca href=\"https:\u002F\u002Fpharmaceutical-journal.com\u002Farticle\u002Ffeature\u002Fhow-ai-is-transforming-drug-discovery\" target=\"_blank\" rel=\"noreferrer noopener\">a drug to treat ulcerative colitis\u003C\u002Fa> that is undergoing clinical trials.\u003C\u002Fp>\n\n\n\n\u003Cp>“Based on the information that’s provided, [the AI model] is able to almost think and propose something that was previously unknown,” Anne Phelan, chief scientific officer at London-based Benevolent AI, \u003Ca href=\"https:\u002F\u002Fpharmaceutical-journal.com\u002Farticle\u002Ffeature\u002Fhow-ai-is-transforming-drug-discovery\" target=\"_blank\" rel=\"noreferrer noopener\">explained to The Pharmaceutical Journal\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Drug formulation\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>A drug’s formulation, or its chemical structure and composition, determines its effectiveness in practice. Algorithms can be used to predict these characteristics of a candidate and whether it will be effective and safe.\u003C\u002Fp>\n\n\n\n\u003Cp>Drug discovery software developer \u003Ca href=\"https:\u002F\u002Fwww.schrodinger.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Schrödinger\u003C\u002Fa> employs AI models to predict how molecules will behave and the possible outcomes, based on their respective parameters. The company’s tools \u003Ca href=\"https:\u002F\u002Fwww.nasdaq.com\u002Farticles\u002Fschrodinger-is-an-ai-powered-drug-discovery-developer-to-watch\" target=\"_blank\" rel=\"noreferrer noopener\">have been adopted\u003C\u002Fa> by pharma companies such as Pfizer and  AstraZeneca.\u003C\u002Fp>\n\n\n\n\u003Cp>Another promising AI tool for drug formulation is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fblog.google\u002Ftechnology\u002Fai\u002Fgoogle-deepmind-isomorphic-alphafold-3-ai-model\u002F\" target=\"_blank\">Google’s AlphaFold\u003C\u002Fa>. The model can accurately predict how potential candidates bind to proteins and influence human disease. Isomorphic Labs \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.isomorphiclabs.com\u002Farticles\u002Frational-drug-design-with-alphafold-3\" target=\"_blank\">utilises AlphaFold\u003C\u002Fa> and its own AI models to improve drug design for projects with its pharmaceutical partners.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"768\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Fai-protein-folding-768x768.png\" alt=\"\" class=\"wp-image-57843\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Fai-protein-folding-768x768.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Fai-protein-folding-150x150.png 150w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Fai-protein-folding.png 1214w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: https:\u002F\u002Fwww.isomorphiclabs.com\u002F\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Drug repurposing\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>As the term suggests, drug repurposing involves employing existing drugs, initially developed for other uses, in new medical applications. This approach can \u003Ca href=\"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Ffull\u002F10.1080\u002F23808993.2024.2393089\" target=\"_blank\" rel=\"noreferrer noopener\">fast-track drug discovery\u003C\u002Fa> cost-effectively. \u003C\u002Fp>\n\n\n\n\u003Cp>Some companies are using AI for such purposes. For example, US-based Recursion has \u003Ca href=\"https:\u002F\u002Fpharmaceutical-journal.com\u002Farticle\u002Ffeature\u002Fhow-ai-is-transforming-drug-discovery\" target=\"_blank\" rel=\"noreferrer noopener\">three repurposed drugs\u003C\u002Fa> undergoing clinical trials and has partnered with Genentech and Bayer for drug discovery.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Technological limitations and ethical challenges to be acknowledged\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Despite the undeniable advantages of AI in aiding drug discovery, there are some limitations to the technology that need to be acknowledged. In particular, the value and reliability of the insights from such models rely on the data used to train them. Some conditions or medical fields such as oncology have more research input and available data; while others, such as tropical diseases, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ft.com\u002Fcontent\u002Fb279d3d4-f1b5-4733-8e64-fcbf90d12219\" target=\"_blank\">might not share\u003C\u002Fa> similar levels of available information. Such gaps in data can be filled over time, but this will require patience and adequate resources. \u003C\u002Fp>\n\n\n\n\u003Cp>Furthermore, the ethical considerations in using such tools must not be overlooked. Companies developing AI for drug discovery must ensure the ethical use of training data and that the outputs are not biased in order to have reliable real-world use.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":245,"protected":16},"\u003Cp>Previously, we contemplated the practical opportunities of the assistance of artificial intelligence (AI) technologies in clinical trials for drug development. Such assistance extends before and […]\u003C\u002Fp>\n",16,40965,{"_acf_changed":16,"footnotes":74},[78,5,250],490,[],[],[],[255,256,257],1607,1621,1833,[259,63,103,104,105,106,107,108,109,260],"post-57841","category-future-of-pharma",{"id":247,"alt_text":262,"caption":74,"description":263,"media_type":124,"media_details":264,"post":276,"source_url":277},"fake drugs counterfeit medicine","Counterfeit medicine, fake drugs, substandard or falsified medication, pills, TMF",{"width":265,"height":266,"file":267,"sizes":268,"image_meta":275},720,405,"2022\u002F03\u002Ffake-drugs2.png",{"medium":269,"thumbnail":272},{"file":270,"width":133,"height":134,"mime-type":135,"source_url":271},"fake-drugs2-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2-370x208.png",{"file":273,"width":146,"height":146,"mime-type":135,"source_url":274},"fake-drugs2-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2-150x150.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},40903,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png",{"cta_type":74,"cta_color":74,"subtitle":74,"key_takeaways":279,"related_books":16,"related_posts_footer":16,"related_posts":16},[280,282,284],{"title":281},"\u003Cp>Drug discovery is the crucial initial stage of drug development but it is typically resource intensive.\u003C\u002Fp>\n",{"title":283},"\u003Cp>Artificial intelligence technologies can aid drug discovery in multiple ways in order to make the process more efficient and precise.\u003C\u002Fp>\n",{"title":285},"\u003Cp>Despite the potentials of the technology, there are still pertinent challenges and the need for ample data to train algorithms for efficient results.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n",{"yoast_wpseo_title":287,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":239},"Drug Discovery In The Age of AI - The Medical Futurist",{"self":289,"collection":294,"about":296,"author":298,"replies":301,"version-history":304,"predecessor-version":307,"wp:featuredmedia":311,"wp:attachment":314,"wp:term":317,"curies":328},[290],{"href":291,"targetHints":292},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57841",{"allow":293},[37],[295],{"href":189},[297],{"href":192},[299],{"embeddable":51,"href":300},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[302],{"embeddable":51,"href":303},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=57841",[305],{"count":71,"href":306},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57841\u002Frevisions",[308],{"id":309,"href":310},60953,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57841\u002Frevisions\u002F60953",[312],{"embeddable":51,"href":313},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F40965",[315],{"href":316},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=57841",[318,320,322,324,326],{"taxonomy":11,"embeddable":51,"href":319},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=57841",{"taxonomy":217,"embeddable":51,"href":321},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=57841",{"taxonomy":220,"embeddable":51,"href":323},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=57841",{"taxonomy":223,"embeddable":51,"href":325},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=57841",{"taxonomy":226,"embeddable":51,"href":327},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=57841",[329],{"name":49,"href":50,"templated":51},{"id":331,"date":332,"date_gmt":333,"guid":334,"modified":336,"modified_gmt":337,"slug":338,"status":62,"type":63,"link":339,"title":340,"content":342,"excerpt":344,"author":71,"featured_media":346,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":347,"categories":348,"tags":352,"project_category":369,"contact_email_category":373,"yst_prominent_words":374,"class_list":385,"better_featured_image":409,"acf":450,"yoast_meta":462,"_links":465},24423,"2026-07-02T06:55:12","2026-07-02T04:55:12",{"rendered":335},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=24423&_wpnonce=e91e46a1c5&status=auto-draft&type=post","2026-07-02T06:55:13","2026-07-02T04:55:13","what-happens-to-your-medical-data-after-you-die","https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-happens-to-your-medical-data-after-you-die",{"rendered":341},"What Happens To Your Medical Data After You Die?",{"rendered":343,"protected":16},"\n\u003Cp>“Almost no one has thought about what is going to happen to all of the medical records that sit around after people die,” \u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\" rel=\"noreferrer noopener\">said Jon Cornwall\u003C\u002Fa>, senior lecturer in the Centre for Early Learning in Medicine at the University of Otago in New Zealand. Indeed, even if death is one of the most certain things in life, we have little control or knowledge about what happens to our collected health data after that point.\u003C\u002Fp>\n\n\n\n\u003Cp>To see for yourself, you could try answering those following questions. How familiar are you with your digital health data footprint? Do you even know about the kind of health data generated about you and where it ends up? And what happens with this ever-growing pile of information after you die? Who owns this data and who can get access to it? Why could this even be interesting and for whom? \u003C\u002Fp>\n\n\n\n\u003Cp>With the advent of digital health technologies such as \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-big-symptom-checker-review\u002F\" target=\"_blank\">chatbots\u003C\u002Fa>, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftop-health-wearables\u002F\" target=\"_blank\">fitness trackers\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmydna-review\u002F\" target=\"_blank\">direct-to-consumer genetic tests\u003C\u002Fa>, that amount of health data soars to new heights with more individual and precise data piling up day by day. It would thus make sense to be able to donate such data; in similar ways we can donate our bodies for science. But it’s not as straightforward as it sounds, and such valuable individualised data are preyed upon by companies.\u003C\u002Fp>\n\n\n\n\u003Cp>We dived into the mainly overlooked area of posthumous medical data and almost got lost. Here are our findings; but just a heads up: it’s messy and complicated.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Little digital breadcrumbs everywhere\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Just as Hansel and Gretel dropped little breadcrumbs along the path in the forest to find their way back home, we leave tons of tiny digital breadcrumbs about ourselves in the digital universe. Facebook posts, e-mails, signing up to newsletters, cookies following our search history, interests, and preferences. The data piles up to form a unique digital identity. In a few decades, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Farticle\u002Fus-global-tech-privacy-trfn\u002Fdata-of-the-dead-virtual-immortality-exposes-holes-in-privacy-laws-idUSKBN21Z0NF?edition-redirect=in\" target=\"_blank\">it is even expected\u003C\u002Fa> that the number of Facebook profiles belonging to dead people will outnumber those of living users. The online space stores everything and never forgets.  \u003C\u002Fp>\n\n\n\n\u003Cp>And what happens with the digital identity after someone’s death? As it certainly creates awkward moments when Facebook signals the birthday of a deceased friend, for example, more and more people realise that the digital era has reached a point where we also have to deal with the digital afterlife. However, so far, it has only created weirdness and confusion. You have online memorial services; \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.thedigitalbeyond.com\u002Fonline-services-list\u002F\" target=\"_blank\">companies who help you plan your digital death\u003C\u002Fa> and afterlife; or even \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.lifenaut.com\u002Flearn-more\u002F\" target=\"_blank\">re-create algorithms\u003C\u002Fa> to make a “digital back-up of their mind”.\u003C\u002Fp>\n\n\n\n\u003Cp>Such endeavours bring us closer to a reality akin to the “Be Right Back” \u003Cem>Black Mirror \u003C\u002Fem>episode where the protagonist “resurrects” her deceased lover in virtual form based on his online communications and profile. Already, social network \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.eter9.com\u002F\" target=\"_blank\">ETER9\u003C\u002Fa> promises to give users “cyber eternity” by pairing them with their A. I. counterparts, which learn their online behaviours and interact on their behalf, even after their demise. It’s still in Beta mode with over 100 000 registered users. The \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftwitter.com\u002Feternime_?lang=en\" target=\"_blank\">Eternime project\u003C\u002Fa> also offers something similar with nearly 47,000 subscribers, but \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Farticle\u002Fus-global-tech-privacy-trfn\u002Fdata-of-the-dead-virtual-immortality-exposes-holes-in-privacy-laws-idUSKBN21Z0NF?edition-redirect=in\" target=\"_blank\">a lack of funding\u003C\u002Fa> put it on hold.\u003C\u002Fp>\n\n\n\n\u003Cp>Who might not be short on funds is a Big Tech company like Microsoft. The latter was \u003Ca href=\"https:\u002F\u002Fwww.popularmechanics.com\u002Ftechnology\u002Frobots\u002Fa35165370\u002Fmicrosoft-resurrects-the-dead-chatbots\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">recently granted a patent\u003C\u002Fa> to develop a chat bot that converses “in the personality of a specific person” based on social data. The company \u003Ca href=\"https:\u002F\u002Fpdfpiw.uspto.gov\u002F.piw?PageNum=0&docid=10853717&IDKey=6E72242A6301&HomeUrl=http%3A%2F%2Fpatft.uspto.gov%2Fnetacgi%2Fnph-Parser%3FSect1%3DPTO2%2526Sect2%3DHITOFF%2526p%3D1%2526u%3D%25252Fnetahtml%25252FPTO%25252Fsearch-bool.html%2526r%3D31%2526f%3DG%2526l%3D50%2526co1%3DAND%2526d%3DPTXT%2526s1%3Dmicrosoft.ASNM.%2526OS%3DAN%2Fmicrosoft%2526RS%3DAN%2Fmicrosoft\" target=\"_blank\" rel=\"noreferrer noopener\">further contemplates\u003C\u002Fa> pairing the technology with a 2D or 3D model of that person. But it’s still “only” a patent, with practical applications, if ever, remaining to be seen.\u003C\u002Fp>\n\n\n\n\u003Cp>Nevertheless, the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-our-brains-health-in-black-mirror\" target=\"_blank\">\u003Cem>Black Mirror \u003C\u002Fem>vibe\u003C\u002Fa> is here and gives us much to contemplate about. Think about it: your grandchildren could converse with the online version of you 40 years from now. And it also raises a host of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fyour-privacy-in-the-digital-health-era-the-medical-futurists-guide\u002F\" target=\"_blank\">privacy concerns\u003C\u002Fa>, now that data is the new oil. Moreover, the digital breadcrumb trail further extends beyond the social media space and into the healthcare space.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>\u003Cstrong>Dr. Frankenstein stitching your medical data\u003C\u002Fstrong>\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Similarly to the digital identity feeding off the breadcrumbs you drop off every time you use the Internet, an ever-growing Frankenstein’s monster evolves out of your medical data. Such data are collected from your birth; but in most cases – and surprisingly enough – this pile of information doesn’t belong to you. Moreover, you don’t have the chance to control it. If you look at the amount of data in question, you will realise the vanity of such an enterprise; and that this is not a far-fetched claim.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1630\" height=\"795\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-Archive.jpg\" alt=\"medical data\" class=\"wp-image-24425\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-Archive.jpg 1630w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-Archive-768x375.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-Archive-1536x749.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-Archive-512x250.jpg 512w\" sizes=\"auto, (max-width: 1630px) 100vw, 1630px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: www.gsb.stanford.edu\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>You get into the universe of medical administration the moment you are born. When you end up in a hospital, medical professionals use charts containing notes and information for diagnosis and treatment. These get into \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.rasmussen.edu\u002Fdegrees\u002Fhealth-sciences\u002Fblog\u002Fhow-long-are-medical-records-kept\u002F\" target=\"_blank\">your (electronic) medical records\u003C\u002Fa>; and every private or public hospital or medical facility where you receive treatment will preserve some medical records of you. These generate \u003Ca href=\"https:\u002F\u002Fwww.rasmussen.edu\u002Fdegrees\u002Fhealth-sciences\u002Fblog\u002Fhow-long-are-medical-records-kept\u002F\">general hea\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.rasmussen.edu\u002Fdegrees\u002Fhealth-sciences\u002Fblog\u002Fhow-long-are-medical-records-kept\u002F\" target=\"_blank\">lth records\u003C\u002Fa> accessible by healthcare professionals; as well as \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.rasmussen.edu\u002Fdegrees\u002Fhealth-sciences\u002Fblog\u002Fhow-long-are-medical-records-kept\u002F\" target=\"_blank\">personal health records\u003C\u002Fa> with details like immunisation history, family medical history and past diagnoses meant for access by patients.\u003C\u002Fp>\n\n\n\n\u003Cp>Now add to that the daily data gathered from digital health technologies from your phone to your smartwatch and the amount gets staggeringly huge. For example, the Marshfield Clinic health system in Wisconsin is on track to store more medical records from deceased patients in its data repository than of living patients \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FVojtech_Huser\u002Fpublication\u002F268431422_Evaluating_the_size_of_deceased_patient_EHR_research_data_sets_A_multi-year_trend_analysis\u002Flinks\u002F546b0da00cf20dedafd3ab7c\u002FEvaluating-the-size-of-deceased-patient-EHR-research-data-sets-A-multi-year-trend-analysis.pdf\" target=\"_blank\">by 2056\u003C\u002Fa>.  As a result of this, millions of posthumous medical records are and will keep sitting around in digital and analogue systems; and that already massive volume is only going to grow. So how do countries deal with those data?\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>\u003Cstrong>The lifetime of health records\u003C\u002Fstrong>\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Looking at this Mount Everest of data and the divergent spaces where it can end up, it seems to be very difficult to take ownership of it – even if you’re alive. The specifics vary from country to country. Moreover, there is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\">no proper framework\u003C\u002Fa> in place for one to pass their health data the way that they wish it to be. \u003C\u002Fp>\n\n\n\n\u003Cp>Currently, record-holders (whether an heir or legal representative) can easily sell such health information to companies interested in mining medical records for their own business interests; they \u003Ca href=\"https:\u002F\u002Fwww.scientificamerican.com\u002Farticle\u002Fhow-data-brokers-make-money-off-your-medical-records\u002F\">only need to remove certai\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.scientificamerican.com\u002Farticle\u002Fhow-data-brokers-make-money-off-your-medical-records\u002F\" target=\"_blank\">n\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.scientificamerican.com\u002Farticle\u002Fhow-data-brokers-make-money-off-your-medical-records\u002F\"> details\u003C\u002Fa> from the records: such as Social Security numbers, names and detailed addresses to protect people’s privacy. Thus, your anonymized medical records can easily end up in a major pharma company’s hands that aims to profit off of real-world evidence for the efficiency of the drugs you happen to use.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1340\" height=\"874\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records.jpg\" alt=\"medical data\" class=\"wp-image-24426\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records.jpg 1340w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-768x501.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FMedical-Records-512x334.jpg 512w\" sizes=\"auto, (max-width: 1340px) 100vw, 1340px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: www.thejournal.ie\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>So what could happen when you are already dead? That’s even more complicated and messy – no matter whether you live in Europe, in the U.S. or in India. Let’s see some examples.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>1. The U.S.\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The situation is the most complicated in the U. S. as there’s no federal law settling even that seemingly simple question: “who owns the patient’s medical records?”. In the States, HIPAA \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Ffor-professionals\u002Fprivacy\u002Fguidance\u002Fhealth-information-of-deceased-individuals\u002Findex.html\" target=\"_blank\">ensures accessibility of health records\u003C\u002Fa> for 50 years after a patient’s death. However, the usual time frame that record-holders keep them for is much shorter and range around \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.rasmussen.edu\u002Fdegrees\u002Fhealth-sciences\u002Fblog\u002Fhow-long-are-medical-records-kept\u002F\" target=\"_blank\">5-10 years after death\u003C\u002Fa>. The law further enables the use of that data, with the access granted by the representatives of the deceased. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>2. The U.K.\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In the U.K., after someone dies, their health records \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nhs.uk\u002Fcommon-health-questions\u002Fnhs-services-and-treatments\u002Fcan-i-access-the-medical-records-health-records-of-someone-who-has-died\u002F\" target=\"_blank\">go to the Primary Care Support England\u003C\u002Fa> for storage; generally for 10 years. Up until that point, personal representatives or someone who has a claim resulting from the death can apply to see the medical records of a deceased person. The NHS can further grant researchers access and use of anonymized health records upon request, while also giving patients the option to opt-out. However, it’s not a law but rather an institutional policy, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\">notes Edina Harbinja\u003C\u002Fa>, a senior lecturer in media and privacy law at Aston University in Birmingham, England.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"700\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FElectronic-health-records.jpg\" alt=\"medical data\" class=\"wp-image-24427\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FElectronic-health-records.jpg 1200w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FElectronic-health-records-768x448.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FElectronic-health-records-512x299.jpg 512w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: www.techengage.com\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>3. Hungary\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftasz.hu\u002Fegeszsegugyi-adatok-gyik\" target=\"_blank\">In Hungary\u003C\u002Fa>, medical records have a relatively long lifespan; as long as 30 years. Discharge summaries’ storage goes for even longer, at least for 50 years. Furthermore, their preservation can extend for even longer if it’s justified by scientific research. When a patient dies, their legal representatives, legal heirs, or close relatives have the right to access their medical records – upon written request. This allows them to know the cause of death or the specificities of their treatment.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>4. India\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>However, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nhp.gov.in\u002Fdata-ownership-of-ehr_mtl\" target=\"_blank\">if you look at India\u003C\u002Fa>, upon the demise of the patient, inactivation of records usually happens after three years and archived permanently. They also note that with the rapid decline in costs of data archiving coupled with the ability to store increasing amounts of data that may be readily accessible, continued maintenance of such data in archives does not lead to any difficulties or disturbances – thus records may be kept indefinitely. That might be a direction that other countries and electronic health records storing systems also take up in the future.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What\nabout tracker data or information from genetic tests?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>While now you can \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftime.com\u002F3706807\u002Ffacebook-death-legacy\u002F\" target=\"_blank\">designate a legacy contact on Facebook\u003C\u002Fa>, you don’t necessarily have that option when it comes to your genetic data. One of the most direct-to-consumer services, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.23andme.com\u002F?myg01=true\" target=\"_blank\">23andMe\u003C\u002Fa>, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fsplinternews.com\u002Fwhat-happens-to-your-genetic-data-when-you-die-1793845957\" target=\"_blank\">previously said that\u003C\u002Fa> they can provide genetic data about a deceased person only to an Executor, Personal Representative or Beneficiary of the deceased’s estate. They also highlighted that those requesting such information must\u003Cem> \u003C\u002Fem>provide evidence and legal documentation indicating they are authorised to act on behalf of the deceased individual. \u003C\u002Fp>\n\n\n\n\u003Cp>But 23andMe also \u003Ca href=\"https:\u002F\u002Fwww.gsk.com\u002Fen-gb\u002Fmedia\u002Fpress-releases\u002Fgsk-and-23andme-sign-agreement-to-leverage-genetic-insights-for-the-development-of-novel-medicines\u002F\">signed a\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.gsk.com\u002Fen-gb\u002Fmedia\u002Fpress-releases\u002Fgsk-and-23andme-sign-agreement-to-leverage-genetic-insights-for-the-development-of-novel-medicines\u002F\" target=\"_blank\"> \u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.gsk.com\u002Fen-gb\u002Fmedia\u002Fpress-releases\u002Fgsk-and-23andme-sign-agreement-to-leverage-genetic-insights-for-the-development-of-novel-medicines\u002F\">$300 million deal\u003C\u002Fa> with pharma giant GSK for drug development. This deal leverages 23andMe’s substantial genetic resources made possible through its customers, who were oblivious that such a deal was in the pipeline. Whether or not such partnerships use the data of deceased customers is unknown.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FGenetic-Data-512x341.jpg\" alt=\"medical data\" class=\"wp-image-24428\"\u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: www.livingdna.com\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Beyond the difficulties of obtaining a deceased person’s genetic data, there are also still many questions about its ownership. Is it shared property as we have a lot in common with our parents or grandparents? Is it legal to take genetic information to the grave if we consider the impact it might have on the life of our descendants? Lawyers and researchers have to figure out many issues around genetic data as it becomes more and more widespread to have a genetic test.\u003C\u002Fp>\n\n\n\n\u003Cp>Regarding fitness trackers, health sensors, or wearables, the issues are very similar. Usually, the user has the option to share their data with one or more persons whom they designate while alive. But usually, they don’t have an option to name a legacy contact. Fitbit’s \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fitbit.com\u002Fglobal\u002Fus\u002Flegal\u002Fprivacy-policy\" target=\"_blank\">privacy policy says nothing\u003C\u002Fa> about what happens upon death; only that you can delete your data. However, it may take up to 90 days to remove all your information.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Can\nyou donate your health data?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Unlike organ donation, ownership of medical data rests in the hands of healthcare providers; without any way of knowing where that ends up. With the detailed, individualised data made available through digital health technologies, there’s scientific value to be had in it. It could help better assess public health issues that require health data over a long timescale. For example, the effect of certain working conditions on the ageing process; or the effects of long term exposure to pollutants.\u003C\u002Fp>\n\n\n\n\u003Cp>“We didn’t find any systems where you could actively give your data,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\">said Jen Krutzinna\u003C\u002Fa>, a bioethicist and a member of the Digital Ethics Lab at the Oxford Internet Institute. “There’s no way to pass it on in a proper way.” Krutzinna is part of a team at the Oxford Internet Institute working on a proposed “\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-04363-6_12\" target=\"_blank\">Ethical Code for Posthumous Medical Data Donation\u003C\u002Fa>”. The framework emphasises that, similar to organ donation, posthumous health data should not be commercially exploited; but rather employed for the common good.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1400\" height=\"1050\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002FDonate-Health-Data.gif\" alt=\"medical data\" class=\"wp-image-24429\"\u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: www.quartz.com\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The Oxford team’s proposed ethical code aims at setting the pace for a process that has yet to materialise. However, it is one that would allow researchers to take advantage of the health data that people leave behind, says Krutzinna. In fact, in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.slideshare.net\u002Fpetrieflom\u002Fjon-cornwall-what-should-happen-to-our-medical-records-when-we-die-140061837\" target=\"_blank\">focus groups conducted by Jon Cornwall\u003C\u002Fa>, participants would agree to have their posthumous medical records handled by the government (rather than private companies); didn’t want the data to be sold; and were also concerned about hacking. “They want anonymity and privacy but want their descendants to have benefits as well,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\">Cornwall said\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>In a similar way, as it gets hard to track where our health information ends up during our lifetime, the issue persists even after our demise. With our increasing digital health data footprint, clear regulations must be set up so that individuals are aware of the options. This also enables them to make informed decisions regarding their medical data after their death. As \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2019\u002F5\u002F28\u002F18642621\u002Fmedical-records-donate-science-digital-data-health-body-death\" target=\"_blank\">Edina Harbinja puts it\u003C\u002Fa>: “We should be able to choose how we dispose of our digital self.”\u003C\u002Fp>\n",{"rendered":345,"protected":16},"\u003Cp>How familiar are you with your digital health data footprint? Do you even know what kind of health data is generated about you and where it is stored? And what happens with this ever-growing pile of information after you die? Who owns this data and who can get access to it? Why could this even be interesting and for whom? We have dived into the mainly overlooked area of posthumous medical data and almost got lost. Here are our findings but just a heads up: it’s messy and complicated.\u003C\u002Fp>\n",24430,{"_acf_changed":16,"footnotes":74},[5,349,350,351],511,521,799,[353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368],1222,686,1286,687,1433,688,1434,196,1435,227,1436,246,275,425,1153,1221,[370,371,93,372],947,951,953,[],[375,376,377,378,379,380,381,382,96,97,383,384],1795,1975,2919,2923,2933,3825,1571,3829,1693,1723,[386,63,103,104,105,106,107,109,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,122,408],"post-24423","category-bioethics","category-future-medicine","category-security-privacy","tag-medical-records","tag-health-data","tag-medical-data","tag-data-privacy","tag-privacy","tag-data-security","tag-health-records","tag-data-2","tag-electronic-medical-records","tag-emr","tag-electronic-health-records","tag-future","tag-healthcare","tag-technology-2","tag-electronic","tag-ehr","project_category-company","project_category-patients","project_category-researchers",{"id":346,"alt_text":410,"caption":411,"description":412,"media_type":124,"media_details":413,"post":331,"source_url":449},"medical data after death","What happens to your medical data after you die?","Do you know what kind of health data is generated about you and where it is stored? And what happens with this of information after you die?",{"width":126,"height":127,"file":414,"sizes":415,"image_meta":447},"2019\u002F07\u002Fhealth_data.png",{"medium":416,"large":421,"thumbnail":426,"medium_large":430,"1536x1536":431,"large_old_512x288":436,"thumbnail_old_150x150":441,"medium_old_370x208":442,"medium_large_old_768x432":443,"large_old_512x288_old_512x288":444},{"file":417,"width":418,"height":419,"mime-type":135,"source_url":420},"health_data-370x208.png",370,208,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data-370x208.png",{"file":422,"width":423,"height":424,"mime-type":135,"source_url":425},"health_data-768x432.png",768,432,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data-768x432.png",{"file":427,"width":428,"height":428,"mime-type":135,"source_url":429},"health_data-150x150.png",150,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data-150x150.png",{"file":422,"width":423,"height":424,"mime-type":135,"source_url":425},{"file":432,"width":433,"height":434,"mime-type":135,"source_url":435},"health_data-1536x864.png",1536,864,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data-1536x864.png",{"file":437,"width":438,"height":439,"mime-type":135,"source_url":440},"health_data-512x288.png",512,288,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data-512x288.png",{"file":427,"width":146,"height":146,"mime-type":135,"source_url":429},{"file":417,"width":133,"height":134,"mime-type":135,"source_url":420},{"file":422,"width":140,"height":141,"mime-type":135,"source_url":425},{"file":437,"width":445,"height":446,"mime-type":135,"source_url":440},"512","288",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":448},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F07\u002Fhealth_data.png",{"related_posts":16,"related_posts_footer":451,"cta_type":166,"cta_color":74,"subtitle":74,"related_books":455,"key_takeaways":457},[452,453,454],23938,13003,13229,[169,456],31417,[458,460],{"title":459},"\u003Cp>What happens to our social media channels and data online when we die?\u003C\u002Fp>\n",{"title":461},"\u003Cp>This article analyzes the special case of our health and medical data being stored in hospitals, at home and at the companies we have purchased technologies and services from.\u003C\u002Fp>\n",{"yoast_wpseo_title":463,"yoast_wpseo_metadesc":464,"yoast_wpseo_canonical":339},"What Happens To Your Medical Data After You Die? - The Medical Futurist","The Medical Futurist dived into the area of posthumous medical data. Here are our findings but just a heads up: it’s messy and complicated.",{"self":466,"collection":471,"about":473,"author":475,"replies":477,"version-history":480,"predecessor-version":484,"wp:featuredmedia":488,"wp:attachment":491,"wp:term":494,"curies":505},[467],{"href":468,"targetHints":469},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F24423",{"allow":470},[37],[472],{"href":189},[474],{"href":192},[476],{"embeddable":51,"href":195},[478],{"embeddable":51,"href":479},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=24423",[481],{"count":482,"href":483},26,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F24423\u002Frevisions",[485],{"id":486,"href":487},60949,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F24423\u002Frevisions\u002F60949",[489],{"embeddable":51,"href":490},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F24430",[492],{"href":493},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=24423",[495,497,499,501,503],{"taxonomy":11,"embeddable":51,"href":496},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=24423",{"taxonomy":217,"embeddable":51,"href":498},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=24423",{"taxonomy":220,"embeddable":51,"href":500},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=24423",{"taxonomy":223,"embeddable":51,"href":502},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=24423",{"taxonomy":226,"embeddable":51,"href":504},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=24423",[506],{"name":49,"href":50,"templated":51},{"id":508,"date":509,"date_gmt":510,"guid":511,"modified":513,"modified_gmt":514,"slug":515,"status":62,"type":63,"link":516,"title":517,"content":519,"excerpt":521,"author":246,"featured_media":523,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":524,"categories":525,"tags":526,"project_category":527,"contact_email_category":528,"yst_prominent_words":529,"class_list":531,"better_featured_image":533,"acf":561,"yoast_meta":569,"_links":571},60901,"2026-06-22T10:00:00","2026-06-22T08:00:00",{"rendered":512},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60901&_wpnonce=756ffd310a&status=auto-draft&type=post","2026-06-19T10:45:13","2026-06-19T08:45:13","are-physicians-losing-skills-due-to-ai-what-is-cognitive-offloading","https:\u002F\u002Fmedicalfuturist.com\u002Fare-physicians-losing-skills-due-to-ai-what-is-cognitive-offloading",{"rendered":518},"Are Physicians Losing Skills Due To AI? What Is Cognitive Offloading?",{"rendered":520,"protected":16},"\n\u003Cp>In the current age of artificial intelligence (AI), physicians are able to rely on the technology for \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcategory\u002Fartificial-intelligence\">a myriad of purposes\u003C\u002Fa>. From triaging patients to assistance with radiological scans, they can turn to AI tools to assist them in their healthcare-related tasks.\u003C\u002Fp>\n\n\n\n\u003Cp>However, by offloading cognitive tasks to automated systems, a new concern has arisen: are doctors losing their clinical skills due to AI? In this article, we reflect on the cognitive offloading phenomenon, its impact on healthcare practice and how clinicians can engage with AI tools without compromising their skills.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What is cognitive offloading?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In general terms, \u003Ca href=\"https:\u002F\u002Fwww.cambridgeassessment.org.uk\u002Fblogs\u002Fcognitive-offloading-in-assessment\u002F\">cognitive offloading involves\u003C\u002Fa> the use of external tools to minimise the mental demands of conducting a task. A classic example is that of using calculators to carry out arithmetic tasks. By using this external tool, we are outsourcing the mental or cognitive need for our brains to do so by itself.\u003C\u002Fp>\n\n\n\n\u003Cp>This process can be applied to a number of tools and, in particular, AI. With this technology, we can offload tasks such as fixing software code to writing whole books. Offloading cognitive tasks to AI is \u003Ca href=\"https:\u002F\u002Fwww.psychologytoday.com\u002Fus\u002Fblog\u002Fthe-digital-self\u002F202606\u002Fai-and-the-psychology-of-cognitive-surrender\">an attractive prospect\u003C\u002Fa> as it offers a low-effort avenue to carry out complex tasks. \u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FTop-AI-companies-768x432.png\" alt=\"A.I. algorithms\" class=\"wp-image-39341\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FTop-AI-companies-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FTop-AI-companies-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FTop-AI-companies-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FTop-AI-companies.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>As with any tool, such task delegation comes with its own benefits and risks. Going back to the calculator analogy, using that tool can help make repetitive calculations easy while a student can rely on more abstract derivations. However, over-reliance on the calculator can also \u003Ca href=\"https:\u002F\u002Fwww.cambridgeassessment.org.uk\u002Fblogs\u002Fcognitive-offloading-in-assessment\u002F\">reduce the student’s ability\u003C\u002Fa> to carry out arithmetic tasks for everyday purposes. \u003C\u002Fp>\n\n\n\n\u003Cp>With cognitive offloading to AI in the healthcare space, the stakes are heightened. The technology is still relatively new, and we need to \u003Ca href=\"https:\u002F\u002Fwww.psychologytoday.com\u002Fus\u002Fblog\u002Fthe-digital-self\u002F202606\u002Fai-and-the-psychology-of-cognitive-surrender\">think about what happens long term\u003C\u002Fa> if AI takes thinking out of physicians’ jobs for months and years.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Cognitive offloading to AI in healthcare: benefits and risks\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Let’s first contemplate the benefits of physicians employing AI for cognitive offloading. In the clinical realm, retrieving and updating medical insights has traditionally been slow and fragmented. Physicians have to navigate through outdated platforms that take away their precious time. AI-driven systems such as \u003Ca href=\"https:\u002F\u002Fwww.hsj.co.uk\u002Ftechnology-and-innovation\u002Fthe-future-of-medical-knowledge-retrieval-reducing-cognitive-load-improving-care\u002F7038841.article\">information retrieval tools\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-much-time-can-ai-scribes-save\">automated scribes\u003C\u002Fa> can handle cognitive tasks to prevent overloading physicians.\u003C\u002Fp>\n\n\n\n\u003Cp>Indeed, some time-consuming tasks such as typing patient encounters in electronic systems can lead to \u003Ca href=\"https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC12678390\u002F\">cognitive overload for physicians\u003C\u002Fa>. In turn, these contribute to \u003Ca href=\"https:\u002F\u002Fwww.uchicagomedicine.org\u002Fforefront\u002Fresearch-and-discoveries-articles\u002Fambient-ai-saves-time-reduces-burnout-fosters-patient-connection\">physician burnout\u003C\u002Fa> while making care delivery \u003Ca href=\"https:\u002F\u002Fwww.hsj.co.uk\u002Ftechnology-and-innovation\u002Fthe-future-of-medical-knowledge-retrieval-reducing-cognitive-load-improving-care\u002F7038841.article\">inefficient\u003C\u002Fa>. AI systems can positively support physicians in routine tasks and improve the care experience.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-768x432.png\" alt=\"\" class=\"wp-image-54109\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>However, there is a delicate balance that needs to be struck with cognitive offloading to AI tools. Becoming too \u003Ca href=\"https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC12678390\u002F#s11\">dependent on these\u003C\u002Fa> can make physicians reduce their autonomy in decision-making and minimise introspection, skills which are key to clinicians.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Fjessepines\u002F2026\u002F02\u002F23\u002Fwill-ai-de-skill-doctors-evidence-is-starting-to-trickle-in\u002F\">Studies indicate\u003C\u002Fa> that doctors who rely heavily on AI output might have their clinical performance negatively impacted. One illustrative example found that endoscopists who regularly use AI assistance experience a notable \u003Ca href=\"https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F40816301\u002F\">decline in detecting\u003C\u002Fa> cancerous lesions (from 29% to 22%) during subsequent non-AI procedures.\u003C\u002Fp>\n\n\n\n\u003Cp>This raises the spectre of “\u003Ca href=\"https:\u002F\u002Fwww.psychologytoday.com\u002Fus\u002Fblog\u002Fthe-digital-self\u002F202606\u002Fai-and-the-psychology-of-cognitive-surrender\">cognitive surrender\u003C\u002Fa>”, the more ominous-sounding consequence of cognitive offloading. As the term implies, this involves fully offloading cognitive tasks to AI, or surrendering all thinking to the tool. In turn, the user \u003Ca href=\"https:\u002F\u002Fpapers.ssrn.com\u002Fsol3\u002Fpapers.cfm?abstract_id=6097646\">can falsely attribute\u003C\u002Fa> the output of these tasks to their own judgement, when, in fact, it is the AI’s.\u003C\u002Fp>\n\n\n\n\u003Cp>It’s a real risk that physicians can succumb to. In particular, for medical students and trainees, these concerns are more relevant. If the next generation of physicians over-rely on AI assistance without critically engaging with their work, \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Fjessepines\u002F2026\u002F02\u002F23\u002Fwill-ai-de-skill-doctors-evidence-is-starting-to-trickle-in\u002F\">they will fail to develop\u003C\u002Fa> the independent problem-solving and diagnostic reasoning skills required for practising.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Can the risks of AI cognitive offloading be mitigated?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>As dire as the consequences of AI cognitive offloading might sound, the practice does not mean a less skilled future clinical workforce. Mitigating the risks also does not rely on a wholesale ban of AI in healthcare. Instead, a more nuanced and critical approach is required.\u003C\u002Fp>\n\n\n\n\u003Cp>If a cognitive task can be fully offloaded to AI – such as outright determining a diagnosis – its usage is \u003Ca href=\"https:\u002F\u002Fwww.cambridgeassessment.org.uk\u002Fblogs\u002Fcognitive-offloading-in-assessment\u002F\">likely inappropriate\u003C\u002Fa>, especially for medical students and trainees. But if the tool can support learners in better engaging with the cognitive task at hand and take over more trivial tasks, then AI can be an adequate complement.\u003C\u002Fp>\n\n\n\n\u003Cp>For example, when analysing a radiological scan, an automated assistance tool \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Fjessepines\u002F2026\u002F02\u002F23\u002Fwill-ai-de-skill-doctors-evidence-is-starting-to-trickle-in\u002F\">could indicate the region \u003C\u002Fa>of a suspicious region and engage the physician in determining the reason for this indication. The latter could even challenge the AI’s thinking, as these tools are not impervious to mistakes.\u003C\u002Fp>\n\n\n\n\u003Cp>As such, AI cognitive offloading \u003Ca href=\"https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC12678390\u002F\">would ideally require\u003C\u002Fa> thoughtful design of the tool, robust policy safeguards, and careful integration. This is no simple task and will require concerted efforts to implement. \u003C\u002Fp>\n\n\n\n\u003Cp>In the meantime, individual physicians can take responsibility to ensure that AI empowers their cognitive tasks rather than erodes their cognitive autonomy by critically engaging with the technology.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":522,"protected":16},"\u003Cp>In the current age of artificial intelligence (AI), physicians are able to rely on the technology for a myriad of purposes. From triaging patients to […]\u003C\u002Fp>\n",60903,{"_acf_changed":16,"footnotes":74},[78,5,350],[],[],[],[257,530],2391,[532,63,103,104,105,106,107,108,109,388],"post-60901",{"id":523,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":534,"post":508,"source_url":560},{"width":535,"height":536,"file":537,"filesize":538,"sizes":539,"image_meta":558},1672,941,"2026\u002F06\u002FAI-and-cognitive-offloading.jpeg",306789,{"medium":540,"large":545,"thumbnail":549,"medium_large":553,"1536x1536":554},{"file":541,"width":418,"height":419,"mime-type":542,"filesize":543,"source_url":544},"AI-and-cognitive-offloading-370x208.jpeg","image\u002Fjpeg",17808,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FAI-and-cognitive-offloading-370x208.jpeg",{"file":546,"width":423,"height":424,"mime-type":542,"filesize":547,"source_url":548},"AI-and-cognitive-offloading-768x432.jpeg",60985,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FAI-and-cognitive-offloading-768x432.jpeg",{"file":550,"width":428,"height":428,"mime-type":542,"filesize":551,"source_url":552},"AI-and-cognitive-offloading-150x150.jpeg",6499,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FAI-and-cognitive-offloading-150x150.jpeg",{"file":546,"width":423,"height":424,"mime-type":542,"filesize":547,"source_url":548},{"file":555,"width":433,"height":434,"mime-type":542,"filesize":556,"source_url":557},"AI-and-cognitive-offloading-1536x864.jpeg",194837,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FAI-and-cognitive-offloading-1536x864.jpeg",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":559},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FAI-and-cognitive-offloading.jpeg",{"subtitle":74,"key_takeaways":562,"cta_type":74,"cta_color":74,"related_books":16,"related_posts_footer":16,"related_posts":16},[563,565,567],{"title":564},"\u003Cp>Usage of artificial intelligence (AI) tools is becoming increasingly prevalent among physicians.\u003C\u002Fp>\n",{"title":566},"\u003Cp>While AI assistance can take repetitive tasks from clinical work, there is a risk that over-relying on these tools can lead to deskilling.\u003C\u002Fp>\n",{"title":568},"\u003Cp>In this article, we take a look at the cognitive offloading phenomenon with AI tools in healthcare and how to mitigate the risks.\u003C\u002Fp>\n",{"yoast_wpseo_title":570,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":516},"Are Physicians Losing Skills Due To AI? What Is Cognitive Offloading? - The Medical Futurist",{"self":572,"collection":577,"about":579,"author":581,"replies":583,"version-history":586,"predecessor-version":590,"wp:featuredmedia":594,"wp:attachment":597,"wp:term":600,"curies":611},[573],{"href":574,"targetHints":575},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60901",{"allow":576},[37],[578],{"href":189},[580],{"href":192},[582],{"embeddable":51,"href":300},[584],{"embeddable":51,"href":585},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60901",[587],{"count":588,"href":589},2,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60901\u002Frevisions",[591],{"id":592,"href":593},60909,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60901\u002Frevisions\u002F60909",[595],{"embeddable":51,"href":596},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60903",[598],{"href":599},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60901",[601,603,605,607,609],{"taxonomy":11,"embeddable":51,"href":602},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=60901",{"taxonomy":217,"embeddable":51,"href":604},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=60901",{"taxonomy":220,"embeddable":51,"href":606},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=60901",{"taxonomy":223,"embeddable":51,"href":608},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=60901",{"taxonomy":226,"embeddable":51,"href":610},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60901",[612],{"name":49,"href":50,"templated":51},{"id":614,"date":615,"date_gmt":616,"guid":617,"modified":619,"modified_gmt":620,"slug":621,"status":62,"type":63,"link":622,"title":623,"content":625,"excerpt":627,"author":71,"featured_media":629,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":630,"categories":631,"tags":632,"project_category":633,"contact_email_category":634,"yst_prominent_words":635,"class_list":641,"better_featured_image":643,"acf":677,"yoast_meta":685,"_links":687},60857,"2026-06-11T11:45:05","2026-06-11T09:45:05",{"rendered":618},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60857&_wpnonce=516bb9d707&status=auto-draft&type=post","2026-06-11T11:45:07","2026-06-11T09:45:07","four-scenarios-of-ai-scribe-adoption-in-healthcare","https:\u002F\u002Fmedicalfuturist.com\u002Ffour-scenarios-of-ai-scribe-adoption-in-healthcare",{"rendered":624},"Four Scenarios of AI Scribe Adoption in Healthcare",{"rendered":626,"protected":16},"\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedical-ai-scribes-in-2025-the-top-3-practical-benefits\">AI scribes\u003C\u002Fa>, the apps that can listen in to the conversations between patients and healthcare professionals and transform them into the exact electronic medical record format the given hospital or practice is using, have taken the healthcare industry by storm. For the past 1-2 years, everyone has been talking about their \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fvoice-to-text-technologies-shape-the-future\">potential\u003C\u002Fa>, technical difficulties in implementation and whether patients and their physicians would be open to using it.\u003C\u002Fp>\n\n\n\n\u003Cp>The potential advantages are obvious: to take over the administrative burden from physicians. This is simply the lowest-hanging fruit in the entire healthcare ecosystem. Just the idea of reducing the time physicians spend on administration is enough to get the attention of anyone in this industry. Studies have been coming out about this aspect and we \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-much-time-can-ai-scribes-save\">analyzed them in detail here\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>The downsides would include the complex IT and legal infrastructure behind care that makes it challenging to just implement such a system into any medical practice. Physicians need to ask for consent from patients before using it, and they still have to learn its tricks to really benefit from AI scribes.\u003C\u002Fp>\n\n\n\n\u003Cp>Keeping all these in mind, I turned to an established futures method, scenario analysis, to gain some insights about how we might want to think about the near future of this technology. For scenario analysis, you need a key driving force that will have a major impact on how changes unfold in our field of interest; and a major uncertainty that might hinder our chances any time to fully exploit its benefits. I chose the following, based on which, you can see the four scenarios and their short descriptions below.\u003C\u002Fp>\n\n\n\n\u003Cp>Key driver: Growing evidence in studies\u003Cbr>Major uncertainty: Acceptance by medical professionals\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"768\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FThe-Near-Future-of-AI-Scribes-in-Medicine-768x768.png\" alt=\"\" class=\"wp-image-60867\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FThe-Near-Future-of-AI-Scribes-in-Medicine-768x768.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FThe-Near-Future-of-AI-Scribes-in-Medicine-150x150.png 150w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F06\u002FThe-Near-Future-of-AI-Scribes-in-Medicine.png 1254w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Scenario #1. Dangerous Hype (High acceptance \u002F Low evidence)\u003C\u002Fh2>\n\n\n\n\u003Cp>Clinicians adopt AI scribes enthusiastically because they promise less administrative burden, better work-life balance and smoother visits with their patients. But the evidence base is still thin: there are studies with varying results. Some show significant time reduction while using the technology, others find nuances only. Therefore, early adoption is driven more by hope, vendor claims and anecdotal relief than proven outcomes. It makes AI scribes a potentially dangerous technology as nothing works without evidence in medicine.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Scenario #2. The End of Administration (High acceptance \u002F High evidence)\u003C\u002Fh2>\n\n\n\n\u003Cp>AI scribes become a normal part of clinical work. I go further than that:it becomes unimaginable to work without them. Studies show clear benefits in documentation quality, clinician satisfaction and workflow efficiency, while physicians see the tool as background infrastructure rather than “AI magic.” Everyone adopts it and using AI scribes is the new medical norm.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Scenario #3. Forever Promise (Low acceptance \u002F Low evidence)\u003C\u002Fh2>\n\n\n\n\u003Cp>AI scribes remain a niche tool. Evidence is weak, and it turns out to be just another AI flop. Clinicians therefore remain skeptical, and concerns about errors, privacy, workflow disruption or patient comfort prevent widespread use. And all these for a reason: no evidence, no adoption.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Scenario #4. Human Obstacle (Low acceptance \u002F High evidence)\u003C\u002Fh2>\n\n\n\n\u003Cp>Studies increasingly show that AI scribes work, but physicians still resist adoption because of trust, liability, patient consent, integration problems, or fear that documentation becomes too automated and less clinically thoughtful. They generally have a trust issue towards AI so only the most enthusiastic physicians keep on using it. Others prefer old methods even if those are slow and burdensome.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Conclusions\u003C\u002Fh2>\n\n\n\n\u003Cp>What we can derive from these scenarios is that if evidence is not growing behind AI scribes in medicine, there is nothing to talk about. But if it is (and it seems it has been growing steadily), the issue we have to work on now is acceptance and adoption by medical professionals. If they are not on board with a technology that can make their jobs better, we will all fail at implementing it.\u003C\u002Fp>\n\n\n\n\u003Cp>So, if a call to action can be summarized, it is that we have to sensitise physicians about AI scribes, otherwise, we will face a long decade of adoption struggles and lag in using an evidence-based and advanced technology for the benefit of patients.\u003C\u002Fp>\n\n\n\n\u003Cp>That’s why I publish so many videos and \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-reasons-physicians-should-get-on-board-with-ai-scribes\">articles about AI scribes for physicians\u003C\u002Fa>.\u003C\u002Fp>\n",{"rendered":628,"protected":16},"\u003Cp>AI scribes, the apps that can listen in to the conversations between patients and healthcare professionals and transform them into the exact electronic medical record […]\u003C\u002Fp>\n",58461,{"_acf_changed":16,"footnotes":74},[5,350],[],[],[],[636,637,98,384,638,257,639,640],4775,1631,1739,2015,3635,[642,63,103,104,105,106,107,109,388],"post-60857",{"id":629,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":644,"post":675,"source_url":676},{"width":645,"height":646,"file":647,"filesize":648,"sizes":649,"image_meta":673},3000,1687,"2025\u002F02\u002Ftmf_article_435.png",352529,{"medium":650,"large":654,"thumbnail":658,"medium_large":662,"1536x1536":663,"2048x2048":667},{"file":651,"width":418,"height":419,"mime-type":135,"filesize":652,"source_url":653},"tmf_article_435-370x208.png",24646,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435-370x208.png",{"file":655,"width":423,"height":424,"mime-type":135,"filesize":656,"source_url":657},"tmf_article_435-768x432.png",61107,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435-768x432.png",{"file":659,"width":428,"height":428,"mime-type":135,"filesize":660,"source_url":661},"tmf_article_435-150x150.png",12448,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435-150x150.png",{"file":655,"width":423,"height":424,"mime-type":135,"filesize":656,"source_url":657},{"file":664,"width":433,"height":434,"mime-type":135,"filesize":665,"source_url":666},"tmf_article_435-1536x864.png",147125,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435-1536x864.png",{"file":668,"width":669,"height":670,"mime-type":135,"filesize":671,"source_url":672},"tmf_article_435-2048x1152.png",2048,1152,211780,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":674},[],58443,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_435.png",{"cta_type":74,"cta_color":74,"subtitle":74,"key_takeaways":678,"related_books":16,"related_posts_footer":16,"related_posts":16},[679,681,683],{"title":680},"\u003Cp>AI scribes, the apps that can listen in to the conversations between patients and healthcare professionals and transform that into the exact electronic medical record format the given hospital or practice is using, have taken the healthcare industry by storm.\u003C\u002Fp>\n",{"title":682},"\u003Cp>I turned to an established futures method, scenario analysis, to gain some insights about how we might want to think about the near future of this technology.\u003C\u002Fp>\n",{"title":684},"\u003Cp>We have to sensitize physicians about AI scribes, otherwise, we will face a long decade of adoption struggles and lag in using an evidence-based and advanced technology for the benefit of patients.\u003C\u002Fp>\n",{"yoast_wpseo_title":686,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":622},"Four Scenarios of AI Scribe Adoption in Healthcare - The Medical Futurist",{"self":688,"collection":693,"about":695,"author":697,"replies":699,"version-history":702,"predecessor-version":705,"wp:featuredmedia":709,"wp:attachment":712,"wp:term":715,"curies":726},[689],{"href":690,"targetHints":691},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60857",{"allow":692},[37],[694],{"href":189},[696],{"href":192},[698],{"embeddable":51,"href":195},[700],{"embeddable":51,"href":701},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60857",[703],{"count":588,"href":704},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60857\u002Frevisions",[706],{"id":707,"href":708},60869,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60857\u002Frevisions\u002F60869",[710],{"embeddable":51,"href":711},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F58461",[713],{"href":714},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60857",[716,718,720,722,724],{"taxonomy":11,"embeddable":51,"href":717},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=60857",{"taxonomy":217,"embeddable":51,"href":719},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=60857",{"taxonomy":220,"embeddable":51,"href":721},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=60857",{"taxonomy":223,"embeddable":51,"href":723},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=60857",{"taxonomy":226,"embeddable":51,"href":725},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60857",[727],{"name":49,"href":50,"templated":51},{"id":729,"date":730,"date_gmt":731,"guid":732,"modified":734,"modified_gmt":735,"slug":736,"status":62,"type":63,"link":737,"title":738,"content":740,"excerpt":742,"author":246,"featured_media":744,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":745,"categories":746,"tags":747,"project_category":748,"contact_email_category":749,"yst_prominent_words":750,"class_list":756,"better_featured_image":758,"acf":791,"yoast_meta":797,"_links":799},58255,"2026-06-04T08:56:31","2026-06-04T06:56:31",{"rendered":733},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=58255&_wpnonce=83a763ce88&status=auto-draft&type=post","2026-06-09T08:05:04","2026-06-09T06:05:04","what-ai-can-already-do-in-healthcare-in-8-examples","https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-ai-can-already-do-in-healthcare-in-8-examples",{"rendered":739},"What AI Can Already Do In Healthcare In 8 Examples",{"rendered":741,"protected":16},"\n\u003Cp>There has been a lot of buzz around artificial intelligence (AI); and the healthcare field is no stranger. The promise of the technology range from \u003Ca href=\"https:\u002F\u002Fhitconsultant.net\u002F2024\u002F11\u002F25\u002Fhealthcare-as-a-right-how-ai-is-shaping-global-access\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">addressing the shortage\u003C\u002Fa> of healthcare providers to \u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Findustries\u002Fhealthcare\u002Four-insights\u002Fgenerative-ai-in-healthcare-adoption-trends-and-whats-next\" target=\"_blank\" rel=\"noreferrer noopener\">improving patient engagement\u003C\u002Fa> in their care. \u003C\u002Fp>\n\n\n\n\u003Cp>Among such promises, it might be challenging to identify the current uses of AI in healthcare. In order to better understand the upcoming potentials of the technology, it is important to understand its current state.\u003C\u002Fp>\n\n\n\n\u003Cp>In this article, we put AI’s current potentials in perspective by sharing a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">1. Generating clinical notes during consultations\u003C\u002Fh2>\n\n\n\n\u003Cp>On average, physicians spend \u003Ca href=\"https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F31931523\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">16 minutes per patient encounter\u003C\u002Fa> on electronic health records. Some of this documentation \u003Ca href=\"https:\u002F\u002Fwww.lyrebirdhealth.com\u002Fuk\u002Fblogs\u002Ftop-4-best-ai-medical-scribes\" target=\"_blank\" rel=\"noreferrer noopener\">can be automated by AI technology\u003C\u002Fa> to save hours for healthcare professionals and also reduce the risk of burnout.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-768x432.png\" alt=\"\" class=\"wp-image-52835\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Real-time transcription and summarization tools like \u003Ca href=\"https:\u002F\u002Fwww.nuance.com\u002Fhealthcare\u002Fdragon-ai-clinical-solutions\u002Fdax-copilot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Nuance’s DAX Copilot\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.lyrebirdhealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Lyrebird Health\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.ambiencehealthcare.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Ambiance\u003C\u002Fa> can automatically document patient encounters. By using speech recognition and natural language processing (NLP), they recognise clinical conversations, extract relevant information and generate summaries. In the case of DAX Copilot, \u003Ca href=\"https:\u002F\u002Fwww.nuance.com\u002Fhealthcare\u002Fdragon-ai-clinical-solutions\u002Fdax-copilot.html\" target=\"_blank\" rel=\"noreferrer noopener\">70% of users report\u003C\u002Fa> improved work-life balance and a reduction in feeling of burnout.\u003C\u002Fp>\n\n\n\n\u003Cp>However, there is \u003Ca href=\"https:\u002F\u002Fapnews.com\u002Farticle\u002Fai-artificial-intelligence-health-business-90020cdf5fa16c79ca2e5b6c4c9bbb14\" target=\"_blank\" rel=\"noreferrer noopener\">the risk of hallucination\u003C\u002Fa> with such tools. This can be a reason for significant concern in a healthcare setting and this highlights the need for the AI summary to be reviewed by humans.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">2. Analysing radiology scans \u003C\u002Fh2>\n\n\n\n\u003Cp>Radiology is among the first medical fields to \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-radiology-and-ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">adopt AI in its midst\u003C\u002Fa>. Companies like \u003Ca href=\"https:\u002F\u002Fwww.aidoc.com\u002Fsolutions\u002Fradiology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Aidoc\u003C\u002Fa> and \u003Ca href=\"http:\u002F\u002Fqure.ai\" target=\"_blank\" rel=\"noreferrer noopener\">Qure.ai\u003C\u002Fa> have developed AI tools that can identify abnormalities in radiology images with high accuracy. \u003C\u002Fp>\n\n\n\n\u003Cp>The AI-driven diagnostics tool from Qure.ai processes \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Ftonybradley\u002F2024\u002F09\u002F29\u002Ftransforming-radiology-with-ai-powered-diagnostics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">around 10 million scans\u003C\u002Fa> every year across more than 90 countries. In the Philippines, the technology has \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Ftonybradley\u002F2024\u002F09\u002F29\u002Ftransforming-radiology-with-ai-powered-diagnostics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">slashed the wait times\u003C\u002Fa> for tuberculosis diagnosis from weeks to seconds.\u003C\u002Fp>\n\n\n\n\u003Cp>Such tools aren’t favoured by every radiologists though, as \u003Ca href=\"https:\u002F\u002Fhms.harvard.edu\u002Fnews\u002Fdoes-ai-help-or-hurt-human-radiologists-performance-depends-doctor\" target=\"_blank\" rel=\"noreferrer noopener\">recent studies\u003C\u002Fa> have shown. AI can help some radiologists’ performance but it can also worsen that of others. This indicates the need to calibrate such tools to individual preference in order to maximise benefits.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">3. Triaging patients \u003C\u002Fh2>\n\n\n\n\u003Cp>Triaging \u003Ca href=\"https:\u002F\u002Fwww.verywellhealth.com\u002Fmedical-triage-and-how-it-works-2615132\" target=\"_blank\" rel=\"noreferrer noopener\">involves the initial assessment\u003C\u002Fa> of patients’ condition to determine their priority of care and the adequate healthcare professional they need to consult. Traditionally, this has been undertaken on a first-come-first-served basis and can take several hours’ of patients’ time. AI tools can make triaging more efficient and equitable based on individual clinical needs.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-768x432.png\" alt=\"medical chatbot AI algorithm person man phone TMF\" class=\"wp-image-48671\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-370x208.png 370w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Tools like \u003Ca href=\"https:\u002F\u002Fada.com\u002Fimproving-patient-pathways-with-ada-digital-triage\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Ada Health\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.rapidhealth.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Rapid Health’s Smart Triage\u003C\u002Fa> use AI to assess symptoms and recommend appropriate care pathways. An \u003Ca href=\"https:\u002F\u002Fwww.med-technews.com\u002Fnews\u002FDigital-in-Healthcare-News\u002Fai-triage-system-achieves-73-reduction-in-waiting-times-according-to-nhs-study\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">independent study\u003C\u002Fa> investigating the Smart Triage system found that the tool reduced patient waiting times by 73%, improved practice capacity and significantly streamlined appointments with sustainable staff working patterns.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">4. Controlling assistive robots\u003C\u002Fh2>\n\n\n\n\u003Cp>In many instances, robots have been adopted as “medical staff” to \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-nurses-superheros-aided-by-technology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">handle monotonous tasks\u003C\u002Fa> and AI can further assist in their tasks. The \u003Ca href=\"https:\u002F\u002Fwww.servicerobotics.ai\u002Frichtech\u002Fmedbot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Medbot\u003C\u002Fa> from Richtech Robotics and Unlimited Robotics’ \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Gary\u003C\u002Fa> are robots that can assist in logistics tasks within healthcare institutions such as delivering medications and general supplies. \u003C\u002Fp>\n\n\n\n\u003Cp>Medbot has an AI platform that helps the robot integrate in the workflow of organisations and streamline operations. Gary, which is also capable of disinfecting hospital rooms, \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">has been found to\u003C\u002Fa> increase nurses’ time with patients and improve staff productivity.\u003C\u002Fp>\n\n\n\n\u003Cp>While such robots can \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002Fpost\u002Frevolutionizing-hospital-inventory-management-how-ai-powered-robotics-can-solve-the-5-billion-prob\" target=\"_blank\" rel=\"noreferrer noopener\">optimise hospitals’ supply chain practices\u003C\u002Fa> and save costs, they might not be accessible to every healthcare institution due to their upfront cost. Depending on hospital size and complexity, the cost to implement a system like Gary can Gary can range \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002Fpost\u002Frevolutionizing-hospital-inventory-management-how-ai-powered-robotics-can-solve-the-5-billion-prob\" target=\"_blank\" rel=\"noreferrer noopener\">between $2–5 million\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">5. Analysing pathology scans and samples\u003C\u002Fh2>\n\n\n\n\u003Cp>In recent years, the field of pathology has received an uplift with the advent of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-future-pathology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">digital pathology\u003C\u002Fa>. This replaces traditional microscope-based manual tissue analyses with \u003Ca href=\"https:\u002F\u002Fhealthcare-in-europe.com\u002Fen\u002Fnews\u002Fdigital-pathology-ai-platform-lung-cancer-diagnosis.html\" target=\"_blank\" rel=\"noreferrer noopener\">digitised tissue sections\u003C\u002Fa> that can be investigated on a computer screen. Such an approach can benefit from AI integration which can be used to apply advanced analytical methods.\u003C\u002Fp>\n\n\n\n\u003Cp>Platforms like \u003Ca href=\"https:\u002F\u002Fpaige.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Paige\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.pathai.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">PathAI\u003C\u002Fa> help pathologists detect cancer and other abnormalities with precision. With Paige’s AI model, pathologists have experienced \u003Ca href=\"https:\u002F\u002Fmeridian.allenpress.com\u002Faplm\u002Farticle\u002F147\u002F10\u002F1178\u002F489438\u002FClinical-Validation-of-Artificial-Intelligence\" target=\"_blank\" rel=\"noreferrer noopener\">up to 70% reduction\u003C\u002Fa> in cancer detection errors. The tool can also reduce the time to diagnosis \u003Ca href=\"https:\u002F\u002Fpathsocjournals.onlinelibrary.wiley.com\u002Fdoi\u002Ffull\u002F10.1002\u002Fpath.5662\" target=\"_blank\" rel=\"noreferrer noopener\">by 65.5%\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers also favour the integration of AI in pathology but \u003Ca href=\"https:\u002F\u002Fdiagnosticpathology.biomedcentral.com\u002Farticles\u002F10.1186\u002Fs13000-023-01375-z\" target=\"_blank\" rel=\"noreferrer noopener\">highlight the need\u003C\u002Fa> to implement the technology under standardized usage recommendations and harmonisation with current information systems.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">6. Detecting risk of falls using video cameras\u003C\u002Fh2>\n\n\n\n\u003Cp>Despite being preventable, falls are a common cause of injury, especially among the elderly. According to the CDC, \u003Ca href=\"https:\u002F\u002Fwww.cdc.gov\u002Ffalls\u002Fdata-research\u002Findex.html\" target=\"_blank\" rel=\"noreferrer noopener\">1 in 4 older adults\u003C\u002Fa> report falling every year which, in some cases, can lead to death. Systems like the AI-powered \u003Ca href=\"https:\u002F\u002Fkamivision.com\u002Fen-us\u002Ffall-detection\u002Fassisted-living-kamicare\" target=\"_blank\" rel=\"noreferrer noopener\">Fall Detection solution by KamiCare\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.averusa.com\u002Fproducts\u002Fptz-camera\u002Fmd720uis\" target=\"_blank\" rel=\"noreferrer noopener\">AVer MD720UIS camera\u003C\u002Fa> monitor movement and assess fall risk in elderly patients. When a fall is detected, the system immediately alerts health teams to respond promptly and ensure patient safety.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed aligncenter is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"High-tech hospital uses artificial intelligence in patient care\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FqetKUFDDF4A?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>As these solutions rely on a camera, privacy concerns arise. Measures that these companies have taken to ensure privacy include blurring faces to only detect movements.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">7. Performing therapy as chatbots \u003C\u002Fh2>\n\n\n\n\u003Cp>Access to mental health services remains a challenge, with such services not reaching \u003Ca href=\"https:\u002F\u002Fwww.news-medical.net\u002Fhealth\u002FArtificial-Intelligence-in-CBT.aspx\" target=\"_blank\" rel=\"noreferrer noopener\">as many as 70%\u003C\u002Fa> needing them. Furthermore, the WHO estimates that high-income countries have \u003Ca href=\"https:\u002F\u002Fwww.who.int\u002Fnews\u002Fitem\u002F08-10-2021-who-report-highlights-global-shortfall-in-investment-in-mental-health\" target=\"_blank\" rel=\"noreferrer noopener\">over 40 times more\u003C\u002Fa> mental health workers than low-income countries. \u003C\u002Fp>\n\n\n\n\u003Cp>To improve access to mental health services, companies have leveraged AI technology. Apps like \u003Ca href=\"https:\u002F\u002Fwoebothealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Woebot\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.wysa.com\u002Fai-cbt\" target=\"_blank\" rel=\"noreferrer noopener\">Wysa\u003C\u002Fa> provide AI-driven cognitive behavioral therapy (CBT) support for patients in need of them. Woebot found that \u003Ca href=\"https:\u002F\u002Fwoebothealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">75% of its users\u003C\u002Fa> employ the app outside of traditional working hours or during weekends. This shows that access to mental health support can be improved when it is needed the most with such AI-based approaches.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"Woebot Demo\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FrrHyFnYWrk4?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>It’s important to note that such apps function\u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fwoebot\" target=\"_blank\" rel=\"noreferrer noopener\"> as support tools\u003C\u002Fa> to be used in tandem with human support. They also won’t cover the whole range of therapies that professionals can provide but they do offer support in a field that is facing severe accessibility challenges.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">8. Predicting patient deterioration in real-time\u003C\u002Fh2>\n\n\n\n\u003Cp>Early signs of patient deterioration can be subtle and challenging for clinical teams to identify. Up to \u003Ca href=\"https:\u002F\u002Fjamanetwork.com\u002Fjournals\u002Fjamanetworkopen\u002Ffullarticle\u002F2824885\" target=\"_blank\" rel=\"noreferrer noopener\">5% of hospitalized patients\u003C\u002Fa> can experience signs of clinical deterioration but delays in adequate care can increase the length of stays or even mortality. \u003C\u002Fp>\n\n\n\n\u003Cp>Tools like the \u003Ca href=\"https:\u002F\u002Fwww.epicshare.org\u002Fshare-and-learn\u002Fsaving-lives-with-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Epic Deterioration Index\u003C\u002Fa> use AI to monitor patient vitals and flag critical conditions in ICUs. In a Novant Health facility, \u003Ca href=\"https:\u002F\u002Fwww.epicshare.org\u002Fshare-and-learn\u002Fsaving-lives-with-ai\">the tool has helped\u003C\u002Fa> reduce mortality by 22% and saved about 153 lives over 11 months.\u003C\u002Fp>\n\n\n\n\u003Cp>Other similar options include \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.agilemd.com\u002F\" target=\"_blank\">eCART from AgileMD\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\">Per\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\" rel=\"noreferrer noopener\">a\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\">Trend from PeraHealth\u003C\u002Fa>. Researchers have even found that eCART can perform \u003Ca href=\"https:\u002F\u002Fjamanetwork.com\u002Fjournals\u002Fjamanetworkopen\u002Ffullarticle\u002F2824885\">better than\u003C\u002Fa> Epic’s tool. We can expect such tools to become even more accurate at determining patients’ health status as their predicting prowess improves over time.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"720\" height=\"405\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png\" alt=\"fake drugs counterfeit medicine\" class=\"wp-image-40965\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png 720w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2-370x208.png 370w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>We hope that you have found these examples where AI is already used in practice insightful! We will be back with another article in this series that focuses on what AI can bring to healthcare in the near future. Stay tuned for it!\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":743,"protected":16},"\u003Cp>In this article, we put AI’s current potentials in perspective by sharing a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n",55953,{"_acf_changed":16,"footnotes":74},[5],[],[],[],[257,751,752,753,381,637,754,98,755],2369,3579,1559,1683,1803,[757,63,103,104,105,106,107,109],"post-58255",{"id":744,"alt_text":759,"caption":74,"description":759,"media_type":124,"media_details":760,"post":789,"source_url":790},"AI, radiology, doctor, X-ray",{"width":761,"height":762,"file":763,"filesize":764,"sizes":765,"image_meta":787},6667,3750,"2024\u002F05\u002Ftmf_article_413.png",570989,{"medium":766,"large":770,"thumbnail":774,"medium_large":778,"1536x1536":779,"2048x2048":783},{"file":767,"width":418,"height":419,"mime-type":135,"filesize":768,"source_url":769},"tmf_article_413-370x208.png",27111,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-370x208.png",{"file":771,"width":423,"height":424,"mime-type":135,"filesize":772,"source_url":773},"tmf_article_413-768x432.png",65695,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-768x432.png",{"file":775,"width":428,"height":428,"mime-type":135,"filesize":776,"source_url":777},"tmf_article_413-150x150.png",16352,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-150x150.png",{"file":771,"width":423,"height":424,"mime-type":135,"filesize":772,"source_url":773},{"file":780,"width":433,"height":434,"mime-type":135,"filesize":781,"source_url":782},"tmf_article_413-1536x864.png",148847,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-1536x864.png",{"file":784,"width":669,"height":670,"mime-type":135,"filesize":785,"source_url":786},"tmf_article_413-2048x1152.png",207612,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":788},[],17898,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413.png",{"subtitle":74,"key_takeaways":792,"cta_type":74,"cta_color":74,"related_books":16,"related_posts_footer":16,"related_posts":16},[793,795],{"title":794},"\u003Cp>With the ongoing buzz around AI’s potential in healthcare, it can be challenging to identify its current uses.\u003C\u002Fp>\n",{"title":796},"\u003Cp>We share a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n",{"yoast_wpseo_title":798,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":737},"What AI Can Already Do In Healthcare In 8 Examples - The Medical Futurist",{"self":800,"collection":805,"about":807,"author":809,"replies":811,"version-history":814,"predecessor-version":818,"wp:featuredmedia":822,"wp:attachment":825,"wp:term":828,"curies":839},[801],{"href":802,"targetHints":803},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F58255",{"allow":804},[37],[806],{"href":189},[808],{"href":192},[810],{"embeddable":51,"href":300},[812],{"embeddable":51,"href":813},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=58255",[815],{"count":816,"href":817},4,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F58255\u002Frevisions",[819],{"id":820,"href":821},60853,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F58255\u002Frevisions\u002F60853",[823],{"embeddable":51,"href":824},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F55953",[826],{"href":827},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=58255",[829,831,833,835,837],{"taxonomy":11,"embeddable":51,"href":830},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=58255",{"taxonomy":217,"embeddable":51,"href":832},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=58255",{"taxonomy":220,"embeddable":51,"href":834},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=58255",{"taxonomy":223,"embeddable":51,"href":836},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=58255",{"taxonomy":226,"embeddable":51,"href":838},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=58255",[840],{"name":49,"href":50,"templated":51},{"id":842,"date":843,"date_gmt":844,"guid":845,"modified":847,"modified_gmt":848,"slug":849,"status":62,"type":63,"link":850,"title":851,"content":853,"excerpt":855,"author":71,"featured_media":629,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":857,"categories":858,"tags":859,"project_category":860,"contact_email_category":861,"yst_prominent_words":862,"class_list":865,"better_featured_image":867,"acf":878,"yoast_meta":886,"_links":888},60757,"2026-05-18T13:00:48","2026-05-18T11:00:48",{"rendered":846},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60757&_wpnonce=ea683fda3e&status=auto-draft&type=post","2026-05-18T13:01:04","2026-05-18T11:01:04","5-reasons-physicians-should-get-on-board-with-ai-scribes","https:\u002F\u002Fmedicalfuturist.com\u002F5-reasons-physicians-should-get-on-board-with-ai-scribes",{"rendered":852},"5 Reasons Physicians Should Get On Board With AI Scribes",{"rendered":854,"protected":16},"\n\u003Cp>Dear physicians, let me ask you a simple question.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>When did documentation become a bigger part of medicine than actually talking to patients?\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>I know. You have heard about \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedical-ai-scribes-in-2025-the-top-3-practical-benefits\">AI scribes\u003C\u002Fa>. You have probably watched explainer videos about what they are, how they listen to the consultation, how they turn the conversation into a structured note, and how they promise to reduce your documentation burden. Maybe you even watched mine.\u003C\u002Fp>\n\n\n\n\u003Cp>But you still have doubts. That is healthy. In medicine, doubt is not a weakness. It is a professional reflex. You should question any technology that enters the clinical encounter, especially one that listens to a conversation between a patient and a physician.\u003C\u002Fp>\n\n\n\n\u003Cp>But here is the point I think we should not miss: AI scribes are not really about AI. They are about giving attention back to patients. That is why I think they might become one of the first healthcare AI tools physicians genuinely want to use.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Because no physician became a physician to become a documentation machine\u003C\u002Fh2>\n\n\n\n\u003Cp>The administrative burden in medicine has become absurd. In one well-known time-motion study in ambulatory care, physicians spent only 27% of their office day on direct clinical face time with patients, while 49.2% went to EHR and desk work. In the examination room itself, more than a third of the time still went to EHR and desk work.\u003C\u002Fp>\n\n\n\n\u003Cp>This is not why people enter medicine. Medical students do not imagine their future careers as a life of clicking boxes, retyping patient stories into templates, and finishing notes after hours. Yet many learn early that modern medicine often means splitting attention between the human being in front of them and the screen beside them.\u003C\u002Fp>\n\n\n\n\u003Cp>And patients feel it too. They can tell when we are present. They can also tell when half of our mind is already preparing the note, checking the medication list, or wondering how much documentation is still waiting at the end of the day.\u003C\u002Fp>\n\n\n\n\u003Cp>The first argument for AI scribes is that the current situation is unacceptable.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"768\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F12\u002F0928_evo_clinical_doc-s-768x768.png\" alt=\"\" class=\"wp-image-58327\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F12\u002F0928_evo_clinical_doc-s-768x768.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F12\u002F0928_evo_clinical_doc-s-150x150.png 150w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F12\u002F0928_evo_clinical_doc-s-1536x1536.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F12\u002F0928_evo_clinical_doc-s-2048x2048.png 2048w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Because the computer should not be the third person in the room\u003C\u002Fh2>\n\n\n\n\u003Cp>The exam room should belong to the patient and the physician. Of course, documentation is necessary. Good notes matter. Continuity of care matters. Legal and billing requirements matter. But somewhere along the way, the computer became too dominant in the clinical encounter.\u003C\u002Fp>\n\n\n\n\u003Cp>AI scribes offer a different model. Instead of typing while the patient speaks, the physician can listen. Instead of translating the conversation into documentation in real time, the physician can focus on the patient’s concerns, emotions, questions and hesitations. The AI scribe drafts the note in the background, and the physician reviews it afterwards.\u003C\u002Fp>\n\n\n\n\u003Cp>That distinction matters. The best digital health technologies are the ones that make medicine feel more human again.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Because mistakes are not a reason to reject them: they are a reason to supervise them\u003C\u002Fh2>\n\n\n\n\u003Cp>Yes, AI scribes make mistakes. They can misunderstand a phrase. They can omit something relevant. They can over-structure a messy conversation. And yes, like other generative AI tools, they can hallucinate.\u003C\u002Fp>\n\n\n\n\u003Cp>This is exactly why no AI-generated note should go into the EHR without physician supervision. But human documentation is not perfect either. Human scribes make mistakes. Assistants make mistakes. Physicians make mistakes. The difference is not whether errors exist. The difference is whether the workflow is designed to catch them.\u003C\u002Fp>\n\n\n\n\u003Cp>The physician remains responsible for the note. That means the physician must review, correct and approve the output. It also means healthcare institutions must take consent, privacy, data governance and auditability seriously. Patients should know when an AI scribe is being used. They should understand what is recorded, how it is processed, and what ends up in the medical record.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Because the evidence is moving in the right direction\u003C\u002Fh2>\n\n\n\n\u003Cp>The early evidence does not show that AI scribes suddenly save every physician two hours a day in every specialty and every setting. But it does \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-much-time-can-ai-scribes-save\">show reductions in documentation\u003C\u002Fa> and EHR time are appearing in real-world settings.\u003C\u002Fp>\n\n\n\n\u003Cp>A large JAMA study across five US academic health systems found that AI scribe adoption was associated with 13.4 fewer minutes of total EHR time and 16.0 fewer minutes of documentation time per 8 scheduled patient hours. The effect was modest overall, but real: and stronger in some groups and workflows.\u003C\u002Fp>\n\n\n\n\u003Cp>Another large European analysis, involving more than 375,000 medical notes generated by 1,295 clinicians, reported that documentation time dropped from 6.69 minutes to 4.71 minutes per note, a 29% reduction.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif\" alt=\"voice to text technologies\" class=\"wp-image-24827\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-370x208.gif 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-1536x864.gif 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-2048x1152.gif 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-512x288.gif 512w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Now, we should not oversell this. A few minutes per note may not sound revolutionary. Thirteen minutes less EHR time per day may not feel like salvation to a physician drowning in bureaucracy. But at scale, these minutes matter.\u003C\u002Fp>\n\n\n\n\u003Cp>They matter across a full clinic day. They matter across a full week. They matter when they reduce after-hours work. They matter when they allow a physician to look a patient in the eye instead of typing through the visit. And this is still an early version of the technology.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Because AI scribes are only the beginning\u003C\u002Fh2>\n\n\n\n\u003Cp>The current AI scribe listens to the encounter and drafts a note. That is useful, but the real future begins when documentation tools become part of a broader AI-supported clinical workflow. Imagine this:\u003C\u002Fp>\n\n\n\n\u003Cp>While the AI scribe summarizes the visit, another approved AI agent retrieves the relevant previous correspondence with this patient. It checks whether the patient emailed about the same symptom last month. It summarizes the last specialist letter. It identifies pending lab results. It prepares a draft follow-up message in patient-friendly language. It does not act autonomously. It prepares the work for the physician to approve.\u003C\u002Fp>\n\n\n\n\u003Cp>Healthcare is full of repetitive, fragmented, low-value administrative tasks. Searching, copying, summarizing, reformatting, re-entering, checking, chasing. These are exactly the tasks AI systems are becoming good at.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">So, should physicians get on board?\u003C\u002Fh2>\n\n\n\n\u003Cp>Physicians should be demanding users of AI scribes. They should test them, challenge them, evaluate them, and insist on safe implementation. They should ask hard questions about privacy, consent, accuracy, liability, integration and workflow.\u003C\u002Fp>\n\n\n\n\u003Cp>AI scribes will not fix burnout or solve workforce shortages alone. They will not make broken EHR systems beautiful overnight. But they can be one meaningful step toward a more humane clinical workflow.\u003C\u002Fp>\n\n\n\n\u003Cp>This way, AI scribes may become one of the first healthcare AI tools clinicians genuinely want to use: not because they are excited about artificial intelligence, but because they want to spend more time being clinicians again.\u003C\u002Fp>\n",{"rendered":856,"protected":16},"\u003Cp>Dear physicians, let me ask you a simple question. When did documentation become a bigger part of medicine than actually talking to patients? I know. […]\u003C\u002Fp>\n",{"_acf_changed":16,"footnotes":74},[5,350],[],[],[],[863,864,257],4661,1593,[866,63,103,104,105,106,107,109,388],"post-60757",{"id":629,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":868,"post":675,"source_url":676},{"width":645,"height":646,"file":647,"filesize":648,"sizes":869,"image_meta":876},{"medium":870,"large":871,"thumbnail":872,"medium_large":873,"1536x1536":874,"2048x2048":875},{"file":651,"width":418,"height":419,"mime-type":135,"filesize":652,"source_url":653},{"file":655,"width":423,"height":424,"mime-type":135,"filesize":656,"source_url":657},{"file":659,"width":428,"height":428,"mime-type":135,"filesize":660,"source_url":661},{"file":655,"width":423,"height":424,"mime-type":135,"filesize":656,"source_url":657},{"file":664,"width":433,"height":434,"mime-type":135,"filesize":665,"source_url":666},{"file":668,"width":669,"height":670,"mime-type":135,"filesize":671,"source_url":672},{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":877},[],{"cta_type":74,"cta_color":74,"subtitle":74,"key_takeaways":879,"related_books":16,"related_posts_footer":16,"related_posts":16},[880,882,884],{"title":881},"\u003Cp>When did documentation become a bigger part of medicine than actually talking to patients?\u003C\u002Fp>\n",{"title":883},"\u003Cp>But here is the point I think we should not miss: AI scribes are about giving attention back to patients.\u003C\u002Fp>\n",{"title":885},"\u003Cp>AI scribes may become one of the first healthcare AI tools clinicians genuinely want to use: not because they are excited about artificial intelligence, but because they want to spend more time being clinicians again.\u003C\u002Fp>\n",{"yoast_wpseo_title":887,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":850},"5 Reasons Physicians Should Get On Board With AI Scribes - The Medical Futurist",{"self":889,"collection":894,"about":896,"author":898,"replies":900,"version-history":903,"predecessor-version":907,"wp:featuredmedia":911,"wp:attachment":913,"wp:term":916,"curies":927},[890],{"href":891,"targetHints":892},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60757",{"allow":893},[37],[895],{"href":189},[897],{"href":192},[899],{"embeddable":51,"href":195},[901],{"embeddable":51,"href":902},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60757",[904],{"count":905,"href":906},1,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60757\u002Frevisions",[908],{"id":909,"href":910},60759,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60757\u002Frevisions\u002F60759",[912],{"embeddable":51,"href":711},[914],{"href":915},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60757",[917,919,921,923,925],{"taxonomy":11,"embeddable":51,"href":918},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=60757",{"taxonomy":217,"embeddable":51,"href":920},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=60757",{"taxonomy":220,"embeddable":51,"href":922},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=60757",{"taxonomy":223,"embeddable":51,"href":924},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=60757",{"taxonomy":226,"embeddable":51,"href":926},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60757",[928],{"name":49,"href":50,"templated":51},{"id":930,"date":931,"date_gmt":932,"guid":933,"modified":935,"modified_gmt":936,"slug":937,"status":62,"type":63,"link":938,"title":939,"content":941,"excerpt":943,"author":71,"featured_media":945,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":946,"categories":947,"tags":948,"project_category":951,"contact_email_category":952,"yst_prominent_words":953,"class_list":960,"better_featured_image":964,"acf":994,"yoast_meta":1010,"_links":1012},54743,"2026-05-11T10:36:27","2026-05-11T08:36:27",{"rendered":934},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=54743&_wpnonce=f04c6c3277&status=auto-draft&type=post","2026-05-11T10:36:28","2026-05-11T08:36:28","will-patients-have-to-pay-for-using-ai-in-their-healthcare","https:\u002F\u002Fmedicalfuturist.com\u002Fwill-patients-have-to-pay-for-using-ai-in-their-healthcare",{"rendered":940},"Will Patients Have To Pay For Using AI In Their Healthcare?",{"rendered":942,"protected":16},"\n\u003Cp>Artificial Intelligence (AI) has become increasingly integral to medical practices, with applications ranging from administrative tasks to diagnostics, patient communication, and logistics optimization. Numerous studies have demonstrated the effectiveness of AI algorithms in daily clinical practice. For instance, AI-assisted mammography and treatment planning have shown promising results in diverse settings, including both \u003Ca href=\"https:\u002F\u002Fwww.lunduniversity.lu.se\u002Farticle\u002Fai-supported-mammography-screening-found-be-safe\" target=\"_blank\" rel=\"noreferrer noopener\">in Sweden\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fhealth.google\u002Fcaregivers\u002Fmammography\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">the U.S\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>In the field of radiotherapy for cancers such as lung, prostate, and colorectal, AI technologies are being harnessed \u003Ca href=\"https:\u002F\u002Fwww.nice.org.uk\u002Fnews\u002Farticle\u002Fartificial-intelligence-technologies-to-speed-up-contouring-in-radiotherapy-treatment-planning\" target=\"_blank\" rel=\"noreferrer noopener\">to accelerate treatment planning\u003C\u002Fa>. This not only reduces the workload for healthcare professionals but also improves patient outcomes – a true win-win scenario we are looking for when designing these studies.\u003C\u002Fp>\n\n\n\n\u003Cp>Artificial intelligence has firmly established its presence in the medical field. The primary consideration is not whether AI will be integrated into standard care, but rather how it will be implemented. Unless one has been metaphorically sleeping through the past year, much like a 21st-century Sleeping Beauty, the rise and relevance of AI in medicine is unmistakable.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Are patients to pay the cost of AI in their care? \u003C\u002Fh2>\n\n\n\n\u003Cp>As AI finds its way into everyday clinical settings, a critical question emerges: who will pay for the deployment (and use and maintenance) of such systems? And this is not a sci-fi question, but something we face today. \u003C\u002Fp>\n\n\n\n\u003Cp>This article discussed how the author was asked \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fedition.cnn.com\u002F2024\u002F01\u002F26\u002Fhealth\u002Fai-mammograms-kff-health-news\u002Findex.html\" target=\"_blank\">if she wanted to pay $40 extra\u003C\u002Fa> for additional AI analysis in mammography. In her case a Manhattan radiology clinic offered an AI analysis of their mammogram for an additional $40, not covered by insurance. This scenario was echoed at a clinic in suburban Baltimore, where patients were similarly offered AI-assisted mammography for a $40 fee. These instances mark the initial real-world applications of AI in patient care but also introduce new factors to the healthcare equation. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png\" alt=\"TMF, medical student, AI, doctor, data, computer\" class=\"wp-image-50547\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>To make things more complicated, we can’t look for a single, universal solution here. Healthcare systems all over the world are extremely diverse, and there will be no “one size fits all” answer that is equally applicable to the private insurance-based model in the USA to the tax-funded public healthcare in Scandinavian countries.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Will AI be cheaper or more expensive than doctors?\u003C\u002Fh2>\n\n\n\n\u003Cp>The question of whether AI will be more cost-effective than traditional medical practices is complex, and the earlier cited examples, where patients were charged extra for AI-assisted mammography, do not necessarily represent a universal pricing model for AI in healthcare. In the future, the cost comparison might not be straightforward and could involve weighing the price of a doctor’s time against the operational costs of an AI algorithm.\u003C\u002Fp>\n\n\n\n\u003Cp>Consider the scenario of laboratory tests. If AI can provide sufficient analysis at a cost of X, and you need to pay 2X for a doctor to review, relying on the algorithm’s assessment becomes a cost-effective option. But of course, it may happen the other way around, it is too early to know that.\u003C\u002Fp>\n\n\n\n\u003Cp>Conversely, while AI might offer an additional layer of analysis for imaging tests like MRIs, this could potentially come at a higher cost. The financial implications of AI in healthcare are still evolving, and it’s unclear how these will reshape overall costs.\u003C\u002Fp>\n\n\n\n\u003Cp>In countries with private insurance-based healthcare systems, the key factor is insurance coverage: will plans adapt to cover AI-enhanced services, and how will this affect premiums and out-of-pocket expenses? In countries with socialised medicine, the question is whether there are sufficient funds to deploy AI technologies in the first place.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-768x432.png\" alt=\"\" class=\"wp-image-50863\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">New divides will be apparent on multiple levels\u003C\u002Fh2>\n\n\n\n\u003Cp>The integration of AI in healthcare, at least in the short term, threatens to create new disparities in access on multiple levels. A clear example is the AI-assisted mammography scenario: those who can afford to pay more receive additional services. Studies show better detection rates with AI, and while the routine value of such technology in clinical practice is still under evaluation, we can take it for granted that access will not be universal.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Within countries\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>You don’t even need to have a private insurance-based system to face this issue. Let’s consider moderately wealthy countries with socialised medicine and healthcare systems – like the B-tier of the developed world. While such nations often boast relatively advanced healthcare systems, their lower GDP results in significantly less funding compared to the wealthiest countries. In such environments, we’ll more likely see AI-assisted solutions in private care, but not (or not much) in the public system.\u003C\u002Fp>\n\n\n\n\u003Cp>This situation also creates disparities: access is often tied to one’s ability to pay. Yet, in these countries, these inequalities are obscured behind the facade of “free healthcare.” This covert inequality is likely to affect many moderately wealthy nations as they struggle to incorporate AI into their public healthcare systems.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Between countries\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Furthermore, we are likely to witness divides between countries and even continents. Wealthier nations with state-funded healthcare systems might introduce AI more rapidly compared to less affluent countries. For instance, Hungary might struggle to keep pace with countries like Sweden or Germany in universally implementing these technologies. \u003C\u002Fp>\n\n\n\n\u003Cp>And of course, there will be a much more pronounced difference between third-world countries and the wealthiest societies. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Between languages\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Languages also present a barrier, as countries speaking languages with a larger global presence, such as English, Chinese, and Spanish will have more readily developed and implemented systems compared to odd, small languages spoken by a few million. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Between wealthy and struggling providers\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>The financial capability to invest in such technologies significantly impacts their availability and implementation. Thus, many systems might become available for some and unavailable to others, like an AI product reducing physician workload and improving efficiency may be more easily adopted by well-funded private clinics than by struggling state healthcare systems. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-768x432.png\" alt=\"\" class=\"wp-image-51075\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_366.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Leapfrogging in the third world? \u003C\u002Fh2>\n\n\n\n\u003Cp>However, there’s an upside: AI could enable ‘leapfrogging’ in less developed countries. These nations might bypass the need for certain intermediate infrastructures that are costly to maintain in developed countries. This could be a stepping stone in their development, potentially turning a previous disadvantage into an opportunity. For example, AI-driven mobile health applications in remote areas could provide diagnostic support where access to healthcare professionals is limited, effectively leapfrogging the need for extensive healthcare infrastructure.\u003C\u002Fp>\n\n\n\n\u003Cp>AI also presents a solution to the shortage of healthcare professionals, a challenge particularly acute in poorer regions. The migration of medical staff to wealthier areas exacerbates this problem, making access to quality healthcare even more challenging. AI could bridge this gap, offering a level of diagnostic and treatment planning support in regions where human resources are scarce.\u003C\u002Fp>\n\n\n\n\u003Cp>Saying all this, it’s clear that the cost of implementing AI in medicine is not a simple issue with straightforward solutions. Healthcare systems worldwide are in a phase of transition, grappling with how best to integrate AI technologies into their frameworks. Regulators, too, face the challenge of establishing guidelines that balance innovation with accessibility and fairness. As patients, we must understand this evolving situation and our options within it. \u003C\u002Fp>\n\n\n\n\u003Cp>Staying informed and engaged is crucial, as these technological advancements hold the potential to significantly alter our healthcare experience. \u003C\u002Fp>\n",{"rendered":944,"protected":16},"\u003Cp>As AI finds its way into everyday clinical settings, a critical question emerges: will patients be asked to pay extra if AI is used in their care? \u003C\u002Fp>\n",54747,{"_acf_changed":16,"footnotes":74},[78,5],[949,950],7671,7673,[],[],[754,954,955,257,956,957,958,959],1709,1715,1835,2293,3061,3189,[961,63,103,104,105,106,107,108,109,962,963],"post-54743","tag-ai-in-healthcare","tag-ai-in-medicine",{"id":945,"alt_text":965,"caption":74,"description":74,"media_type":124,"media_details":966,"post":930,"source_url":993},"AI, radiomics, radiology, X-ray",{"width":761,"height":762,"file":967,"filesize":968,"sizes":969,"image_meta":991},"2024\u002F02\u002Ftmf_article_399.png",1452526,{"medium":970,"large":974,"thumbnail":978,"medium_large":982,"1536x1536":983,"2048x2048":987},{"file":971,"width":418,"height":419,"mime-type":135,"filesize":972,"source_url":973},"tmf_article_399-370x208.png",32741,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-370x208.png",{"file":975,"width":423,"height":424,"mime-type":135,"filesize":976,"source_url":977},"tmf_article_399-768x432.png",95248,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-768x432.png",{"file":979,"width":428,"height":428,"mime-type":135,"filesize":980,"source_url":981},"tmf_article_399-150x150.png",11919,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-150x150.png",{"file":975,"width":423,"height":424,"mime-type":135,"filesize":976,"source_url":977},{"file":984,"width":433,"height":434,"mime-type":135,"filesize":985,"source_url":986},"tmf_article_399-1536x864.png",252017,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-1536x864.png",{"file":988,"width":669,"height":670,"mime-type":135,"filesize":989,"source_url":990},"tmf_article_399-2048x1152.png",379272,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":992},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399.png",{"cta_type":166,"cta_color":74,"related_books":995,"related_posts_footer":999,"related_posts":16,"subtitle":74,"key_takeaways":1003},[996,997,998],24765,24761,52203,[1000,1001,1002],54593,54615,54533,[1004,1006,1008],{"title":1005},"\u003Cp>AI solutions are expensive to develop, especially in the healthcare setting.\u003C\u002Fp>\n",{"title":1007},"\u003Cp>There is an ongoing debate about who would pay for the advanced use of AI in diagnosis and decision-making.\u003C\u002Fp>\n",{"title":1009},"\u003Cp>We see examples where patients are offered a chance to “upgrade” their care with AI, but they have to pay for it themselves.\u003C\u002Fp>\n",{"yoast_wpseo_title":940,"yoast_wpseo_metadesc":1011,"yoast_wpseo_canonical":938},"As AI finds its way into everyday clinical settings, a critical question emerges: will patients be asked to pay extra if AI is used in their healthcare?",{"self":1013,"collection":1018,"about":1020,"author":1022,"replies":1024,"version-history":1027,"predecessor-version":1031,"wp:featuredmedia":1035,"wp:attachment":1038,"wp:term":1041,"curies":1052},[1014],{"href":1015,"targetHints":1016},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54743",{"allow":1017},[37],[1019],{"href":189},[1021],{"href":192},[1023],{"embeddable":51,"href":195},[1025],{"embeddable":51,"href":1026},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=54743",[1028],{"count":1029,"href":1030},14,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54743\u002Frevisions",[1032],{"id":1033,"href":1034},54779,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54743\u002Frevisions\u002F54779",[1036],{"embeddable":51,"href":1037},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F54747",[1039],{"href":1040},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=54743",[1042,1044,1046,1048,1050],{"taxonomy":11,"embeddable":51,"href":1043},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=54743",{"taxonomy":217,"embeddable":51,"href":1045},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=54743",{"taxonomy":220,"embeddable":51,"href":1047},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=54743",{"taxonomy":223,"embeddable":51,"href":1049},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=54743",{"taxonomy":226,"embeddable":51,"href":1051},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=54743",[1053],{"name":49,"href":50,"templated":51},{"id":1055,"date":1056,"date_gmt":1057,"guid":1058,"modified":1060,"modified_gmt":1061,"slug":1062,"status":62,"type":63,"link":1063,"title":1064,"content":1066,"excerpt":1068,"author":71,"featured_media":1070,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1071,"categories":1072,"tags":1073,"project_category":1076,"contact_email_category":1078,"yst_prominent_words":1079,"class_list":1081,"better_featured_image":1086,"acf":1115,"yoast_meta":1130,"_links":1132},55673,"2026-05-11T10:34:09","2026-05-11T08:34:09",{"rendered":1059},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=55673&_wpnonce=75c5bf66e8&status=auto-draft&type=post","2026-05-11T10:34:10","2026-05-11T08:34:10","what-if-generative-ai-turned-to-be-a-flop-in-healthcare","https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-if-generative-ai-turned-to-be-a-flop-in-healthcare",{"rendered":1065},"What If Generative AI Turned To Be A Flop In Healthcare?",{"rendered":1067,"protected":16},"\n\u003Cp>The excitement surrounding generative AI is reaching a fever pitch. From tech giants to healthcare leaders, \u003Ca href=\"https:\u002F\u002Fwww.cbinsights.com\u002Fresearch\u002Fgenerative-ai-funding-top-startups-investors-2023\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">investment \u003C\u002Fa>in this seemingly game-changing technology is exploding. We’re embracing the trend: we’ve written \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fsearch\u002F?term=AI\" target=\"_blank\" rel=\"noreferrer noopener\">dozens of articles\u003C\u002Fa>, created multiple videos, published \u003Ca href=\"https:\u002F\u002Fleanpub.com\u002Fgenerative-ai-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">an ebook\u003C\u002Fa>, and recently launched a \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.thinkific.com\u002Fcourses\u002Fshort-guide-to-generative-ai-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">new short course\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>However, amidst the enthusiasm, AI expert Gary Marcus \u003Ca href=\"https:\u002F\u002Fcacm.acm.org\u002Fblogcacm\u002Fwhat-if-generative-ai-turned-out-to-be-a-dud\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">raised an important question\u003C\u002Fa> a few months ago: What if, for all its promise, generative AI fails to deliver long-term? While he outlined the pessimistic scenario in general, I wanted to dissect what genAI being a flop would mean in healthcare and medicine.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">How to define generative AI failure in healthcare?\u003C\u002Fh2>\n\n\n\n\u003Cp>Since the public launch of ChatGPT, we’ve \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fsearch\u002F?term=chatgpt\" target=\"_blank\" rel=\"noreferrer noopener\">explored the potential of generative AI\u003C\u002Fa> in medicine. This technology offers \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fusing-chatgpt-offline-the-emergence-of-small-language-models\" target=\"_blank\" rel=\"noreferrer noopener\">promising applications\u003C\u002Fa>, from enhancing administrative efficiency to functioning \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-evolution-of-clinical-documentation-from-paper-to-ai\" target=\"_blank\" rel=\"noreferrer noopener\">as a virtual medical scribe\u003C\u002Fa>, potentially reshaping how medical facilities operate and interact with patients.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh7-us.googleusercontent.com\u002FJVJmk_7AuL0GceA0LMbj64Ly95EUeuLUzI-_Emsny7HFIULvqP5-4y-7yAMNg0GpxinGdBsiIeR2VsrOBJ_D2s8v3YZcHlBAgGsA_k_USM1LvFBRiFL71hVcKr45oMtCR1A3SGljTPhWjF4K5C-iVN0\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Let’s now consider the other side of the coin. If generative AI fails to live up to the expectations, the consequences for healthcare could be significant. Let’s break down what failure could look like.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>We don’t find evidence that it works\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>A fundamental failure of generative AI would be its inability to be incorporated into evidence-based medicine. Without robust empirical support from well-conducted research and clinical trials, AI technologies can’t be applied in medical practice. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>No clinical trials prove its safety\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Similarly, a major red flag will be if years go by and we don’t see solid clinical trials to evaluate the potential of generative AI.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>And\u002For find proof that it’s useless\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Another clear indicator would be if trials, pilots, and studies would prove that using generative AI in healthcare is inefficient and\u002For unsafe. This could mean AI systems making inaccurate predictions, leading to incorrect treatments, or compromising patient privacy and safety, ultimately causing more harm than good.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Deep fakes rule the information highways\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>The use of AI to create deep fakes could provoke significant ethical concerns and public outrage. This could include being used to falsify medical records, create misleading patient data, deepfake medical authorities \u003Ca href=\"https:\u002F\u002Findianexpress.com\u002Farticle\u002Fcities\u002Fdelhi\u002Fvideo-medanta-hospital-chief-weight-loss-deepfake-gurgaon-police-9223387\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">advocating bogus treatments\u003C\u002Fa> or arguing against clinically proven ones, or fabricating medical advice. These could be life-threatening scenarios, and right now we are not exactly sure how to ensure such content can’t reach the general population. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh7-us.googleusercontent.com\u002FkUdEtFuynGoJgscKhz11Ulrg4iM_Alg-FgThq4WWbcHkpmKRKXmzm0DOuBYzBma76UNRXiFcYGpaJvGTRAcDQ-Sft9u2D433L5eurYla-yjpYPCVhKLxmLqCz3Ilfl7x_QNtz_tS_pBvCgFvbeXz6Pc\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>\u003Cstrong>People recognize AI text and don’t find it credible enough\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>As the novelty of generative AI may wane, AI-generated materials – brochures, summaries, etc. – become easily distinguishable and may be seen as less credible and unreliable. Thus generative AI as a tool for creating legitimate medical content could diminish.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">What happens next?\u003C\u002Fh2>\n\n\n\n\u003Cp>Continuing from the potential pitfalls of generative AI in healthcare, let’s explore the broader implications should these technologies fail to fulfill their promises. The consequences would ripple across the healthcare industry affecting public trust, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-current-state-of-fda-approved-ai-based-medical-devices\" target=\"_blank\" rel=\"noreferrer noopener\">regulatory landscapes\u003C\u002Fa>, and investment dynamics.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Erosion of trust\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Generative AI’s failure to deliver on its promises could erode public trust in AI applications in general, casting doubt on its reliability and effectiveness. This could also slow the adoption of other AI-powered tools in healthcare and beyond.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Leading to bans\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>If generative AI is unsafe or ineffective in healthcare, regulatory bodies might impose restrictions or bans on its use in sensitive environments such as medical schools and hospitals. Such prohibitions would be a protective measure to prevent harm and preserve the integrity of medical education and patient care, but they would also hinder development and limit the technology’s potential benefits.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh7-us.googleusercontent.com\u002FFGTbpW58nRxxDh5KoRGRQMt_fVJvMsrfCng14uVSIw-eUifGhOaADJjJdqtIQ0rf3D4EkEY_Cwi9GoHhpd2QKJh_6ZTudAlIX6KyZfs7euQOn01VUZY8GIHVpfEj-wi9JAJH2lbuF0181Y73cYKtb-I\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>\u003Cstrong>Overly stringent regulations\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>In response to potential risks, policymakers might introduce overly stringent regulations, stifling innovation and halting the development of generative AI in healthcare. This could create a bureaucratic quagmire, slowing progress and discouraging investment.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Investors turn away from the field\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>If generative AI fails to demonstrate clear value, investors might lose confidence and pull back their funding. This could lead to a decline in research and development, further delaying or even halting progress in this field.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">However, I don’t think it is a flop\u003C\u002Fh2>\n\n\n\n\u003Cp>Having said all that, I still don’t believe generative AI will be a flop in medicine (or elsewhere). It is different from previous technologies in a crucial way: we don’t need to believe how it works to a handful of experts working in specialised labs. Quite the contrary, we can directly interact with and test it, experiment, and discover its potential. Still, thinking about “what if” questions is rarely a waste of time, as it helps us prepare for the future.\u003C\u002Fp>\n\n\n\n\u003Cp>I think the very nature of generative AI – its accessibility and the ability for daily hands-on use – suggests that it is unlikely to fail outright. Instead, my greater concern lies with its potentially rapid, unregulated development, which could lead to unforeseen consequences and challenges. \u003C\u002Fp>\n",{"rendered":1069,"protected":16},"\u003Cp>What if generative AI fails to live up to the expectations? The consequences for healthcare could be significant. Let’s analyze the worst-case scenario!\u003C\u002Fp>\n",55731,{"_acf_changed":16,"footnotes":74},[78,5],[1074,85,1075],7933,7691,[1077,92,93,372],949,[],[256,754,384,1080,257,956],1831,[1082,63,103,104,105,106,107,108,109,1083,115,1084,1085,121,122,408],"post-55673","tag-generative-ai","tag-ai-in-heaalthcare","project_category-educators",{"id":1070,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":1087,"post":1055,"source_url":1114},{"width":761,"height":762,"file":1088,"filesize":1089,"sizes":1090,"image_meta":1112},"2024\u002F04\u002Ftmf_article_410.png",1977566,{"medium":1091,"large":1095,"thumbnail":1099,"medium_large":1103,"1536x1536":1104,"2048x2048":1108},{"file":1092,"width":418,"height":419,"mime-type":135,"filesize":1093,"source_url":1094},"tmf_article_410-370x208.png",44354,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410-370x208.png",{"file":1096,"width":423,"height":424,"mime-type":135,"filesize":1097,"source_url":1098},"tmf_article_410-768x432.png",119375,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410-768x432.png",{"file":1100,"width":428,"height":428,"mime-type":135,"filesize":1101,"source_url":1102},"tmf_article_410-150x150.png",20270,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410-150x150.png",{"file":1096,"width":423,"height":424,"mime-type":135,"filesize":1097,"source_url":1098},{"file":1105,"width":433,"height":434,"mime-type":135,"filesize":1106,"source_url":1107},"tmf_article_410-1536x864.png",293632,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410-1536x864.png",{"file":1109,"width":669,"height":670,"mime-type":135,"filesize":1110,"source_url":1111},"tmf_article_410-2048x1152.png",425355,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":1113},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_410.png",{"cta_type":166,"cta_color":74,"related_books":1116,"related_posts_footer":1119,"related_posts":16,"subtitle":74,"key_takeaways":1123},[998,1117,1118],55605,24759,[1120,1121,1122],55573,55379,55115,[1124,1126,1128],{"title":1125},"\u003Cp>If generative AI fails to demonstrate effectiveness and safety through clinical trials and empirical evidence, it risks exclusion from evidence-based medical practice\u003C\u002Fp>\n",{"title":1127},"\u003Cp>A failure of generative AI could erode public trust, provoke ethical concerns with deepfakes, and lead to stringent regulations or outright bans in medical settings, potentially stifling further innovation and investment in the field.\u003C\u002Fp>\n",{"title":1129},"\u003Cp>Although I predict the success of generative AI due to its accessibility and usability, analyzing “what if” scenarios is always important as it helps to prepare for future challenges.\u003C\u002Fp>\n",{"yoast_wpseo_title":1065,"yoast_wpseo_metadesc":1131,"yoast_wpseo_canonical":1063},"What if generative AI fails to live up to the expectations? The consequences for healthcare could be significant. Let's analyze the worst-case scenario!",{"self":1133,"collection":1138,"about":1140,"author":1142,"replies":1144,"version-history":1147,"predecessor-version":1151,"wp:featuredmedia":1155,"wp:attachment":1158,"wp:term":1161,"curies":1172},[1134],{"href":1135,"targetHints":1136},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55673",{"allow":1137},[37],[1139],{"href":189},[1141],{"href":192},[1143],{"embeddable":51,"href":195},[1145],{"embeddable":51,"href":1146},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=55673",[1148],{"count":1149,"href":1150},7,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55673\u002Frevisions",[1152],{"id":1153,"href":1154},55749,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55673\u002Frevisions\u002F55749",[1156],{"embeddable":51,"href":1157},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F55731",[1159],{"href":1160},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=55673",[1162,1164,1166,1168,1170],{"taxonomy":11,"embeddable":51,"href":1163},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=55673",{"taxonomy":217,"embeddable":51,"href":1165},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=55673",{"taxonomy":220,"embeddable":51,"href":1167},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=55673",{"taxonomy":223,"embeddable":51,"href":1169},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=55673",{"taxonomy":226,"embeddable":51,"href":1171},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=55673",[1173],{"name":49,"href":50,"templated":51},{"id":1175,"date":1176,"date_gmt":1177,"guid":1178,"modified":1180,"modified_gmt":1181,"slug":1182,"status":62,"type":63,"link":1183,"title":1184,"content":1186,"excerpt":1188,"author":71,"featured_media":1190,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1191,"categories":1192,"tags":1193,"project_category":1199,"contact_email_category":1200,"yst_prominent_words":1201,"class_list":1209,"better_featured_image":1216,"acf":1237,"yoast_meta":1251,"_links":1253},56571,"2026-04-30T10:23:18","2026-04-30T08:23:18",{"rendered":1179},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=56571&_wpnonce=6b6a915dc6&status=auto-draft&type=post","2026-04-30T10:23:20","2026-04-30T08:23:20","the-ai-and-digital-health-future-of-pharma-prescription-for-change","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-ai-and-digital-health-future-of-pharma-prescription-for-change",{"rendered":1185},"The AI And Digital Health Future Of Pharma: Prescription For Change",{"rendered":1187,"protected":16},"\n\u003Cp>Over the past decade, our lead researcher, Dr. Bertalan Meskó, has delivered hundreds of keynote speeches to leading pharmaceutical companies worldwide. As The Medical Futurist, he spends his days mapping out the future of healthcare, a complex and fascinating task. And while his work covers all facets of medicine, from regulation and policies to clinical work, research, and technological development, the pharma sector is probably the one he has spent most of his time on in the past 15 years. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Major current digital health and AI trends in pharma\u003C\u002Fh2>\n\n\n\n\u003Cp>Over the years, he has identified some clear trends that will shape the future of the pharmaceutical landscape. Some of these trends are unmistakably on the horizon, others present a more speculative glimpse into what may come. In this article, we will explore both the obvious and the less certain impacts of the digital health and AI revolution on the pharma industry – as seen in 2024.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Using AI in low-risk, high-ROI fields\u003C\u002Fh3>\n\n\n\n\u003Cp>One of the most promising applications of AI in the pharmaceutical industry is in low-risk, high-return-on-investment (ROI) fields such as:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>drug design, \u003C\u002Fli>\n\n\n\n\u003Cli>drug repurposing, \u003C\u002Fli>\n\n\n\n\u003Cli>and clinical trials. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>In drug design, AI algorithms can analyse vast datasets to identify potential drug candidates more quickly and accurately than traditional methods. \u003C\u002Fp>\n\n\n\n\u003Cp>Bristol Myers Squibb \u003Ca href=\"https:\u002F\u002Fwww.fiercebiotech.com\u002Fbiotech\u002Fbristol-myers-pays-exscientia-20m-1-2b-deal-for-first-drug-candidate\">has partnered with Exscientia\u003C\u002Fa> to use AI for small-molecule drug discovery. The collaboration will use AI to accelerate the discovery of small-molecule therapeutic drug candidates in multiple therapeutic areas, including oncology & immunology. The company also announced \u003Ca href=\"https:\u002F\u002Finvestors.exscientia.ai\u002Fpress-releases\u002Fpress-release-details\u002F2023\u002FExscientia-Announces-Expansion-of-its-Current-Collaboration-with-Sanofi-to-Include-Existing-Exscientia-Programme\u002Fdefault.aspx\">a collaboration with Sanofi\u003C\u002Fa> in 2023. \u003C\u002Fp>\n\n\n\n\u003Cp>Merck forged AI drug-development collaborations with American-Israeli biotech company Biolojic Design and with U.S. company Caris Life Sciences. In September 2023, the company started working with U.K.-based AI specialists BenevolentAI and Exscientia, aiming to significantly reduce drug discovery timelines – \u003Ca href=\"https:\u002F\u002Fwww.wsj.com\u002Ftech\u002Fbiotech\u002Fgermanys-merck-bets-on-ai-drug-design-partnerships-rules-out-acquisitions-interview-943c5b7a\">The Wall Street Journal reported\u003C\u002Fa> in June 2024. \u003C\u002Fp>\n\n\n\n\u003Cp>Clinical trials alone are a vast field for AI, we \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fai-assistance-in-clinical-trials-the-practical-opportunities\">recently analysed this segment\u003C\u002Fa> and listed examples of how various algorithms can be used in pre-trial assistance, how they can support trials, and what they can do after the trials. Tools like \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-promise-of-crispr-gpt-specialized-chatgpts-could-transform-medicine\">CRISPR-GPT\u003C\u002Fa> can help us automate trial designs. In-silico platforms can predict real-world results with high accuracy. Novadiscovery’s jinkō \u003Ca href=\"https:\u002F\u002Fwww.novadiscovery.com\u002Fnovadiscovery-announces-success-of-first-of-its-kind-clinical-trial-simulation-to-accurately-predict-findings-of-phase-iii-clinical-study\u002F#:~:text=The%20jink%C5%8D%2Dpredicted%20findings%20were,a%20median%20TTP%20of%2025.9%20%5B\">predicted the results of an AstraZeneca trial\u003C\u002Fa> with about 97% accuracy before the company published the results. And it took three weeks to design, one hour to execute – and had a cost of a couple thousand dollars.\u003C\u002Fp>\n\n\n\n\u003Cp>Here is an excellent confirmation that \u003Ca href=\"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS135964462400134X\">AI-generated drugs can indeed perform well\u003C\u002Fa> in clinical trials. “In Phase I, we find AI-discovered molecules have an 80–90% success rate, substantially higher than historic industry averages. In Phase II the success rate is ∼40%, albeit on a limited sample size, comparable to historic industry averages.”\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"799\" height=\"629\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F06\u002F1715598207270.jpg\" alt=\"AI drug discovery\" class=\"wp-image-56573\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F06\u002F1715598207270.jpg 799w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F06\u002F1715598207270-768x605.jpg 768w\" sizes=\"auto, (max-width: 799px) 100vw, 799px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Using generative AI to enhance company processes\u003C\u002Fh3>\n\n\n\n\u003Cp>Pharmaceutical companies are not only using AI to discover new therapies but also to optimize their internal operations. Roche, for instance, has \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fposts\u002Fdavedrodge_chatgpt-health-rochegpt-activity-7111805972209090561-ATUk\u002F\">introduced RocheGPT,\u003C\u002Fa> an internal generative AI chatbot designed to streamline repetitive tasks, help intra-team knowledge sharing, and augment analysts’ efforts by analysing scientific articles or clinical test results and then extracting structured data about therapies and patients. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">From patient centricity slowly to patient design\u003C\u002Fh3>\n\n\n\n\u003Cp>The traditional pharma landscape has often operated with a paternalistic “we are making decisions about you” attitude towards patients. However, this dynamic is gradually shifting towards a more collaborative “we are making decisions with you” approach. \u003Ca href=\"https:\u002F\u002Fwww.jmir.org\u002F2022\u002F8\u002Fe39178\">This evolution\u003C\u002Fa> is driven by the growing recognition that patients are not supposed to be just passive recipients of care, but active members of their health team.\u003C\u002Fp>\n\n\n\n\u003Cp>Patient design involves patients as co-creators in the design and development of healthcare solutions. And this is certainly something the vast \u003Ca href=\"https:\u002F\u002Fnewsroom.accenture.com\u002Fnews\u002F2014\u002Fpatients-expect-pharmaceutical-companies-to-provide-services-that-help-them-manage-their-health-accenture-survey-finds\">majority of patients want\u003C\u002Fa>. In the past decade or so, policy makers started adopting this theme too. The US Food and Drug Administration (FDA) launched the \u003Ca href=\"https:\u002F\u002Fwww.fda.gov\u002Fabout-fda\u002Fdivision-patient-centered-development\u002Fcdrh-patient-engagement-advisory-committee\">Patient Engagement Advisory Committee\u003C\u002Fa> in 2017. The committee provides advice to the FDA commissioner or designee on complex issues relating to medical devices, the regulation of devices, and their use by patients.\u003C\u002Fp>\n\n\n\n\u003Cp>This shift is long overdue. After all, patients are the ultimate “customers” of healthcare, and their experiences and needs should be at the forefront of every decision. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Automating the supply chain\u003C\u002Fh3>\n\n\n\n\u003Cp>The pharmaceutical supply chain is undergoing a significant transformation through the integration of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Frobotics-blockchain-redesign-pharma-supply-chain\u002F\">robotics, AI, and blockchain technology\u003C\u002Fa>. These advancements streamline operations, enhance efficiency, and ensure greater transparency and security. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_270-01-768x432.png\" alt=\"TMF, drug, flu, woman, cold\" class=\"wp-image-34583\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_270-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_270-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_270-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_270-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>For example, robotics can automate repetitive tasks such as sorting, packaging, and labeling medications, minimizing the risk of human error and freeing up personnel for more complex tasks. While fake drugs are increasingly becoming a problem all over the world (yes, in developed countries too), technology \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffighting-fake-drugs-with-miniscule-printed-watermarks-a-genius-idea\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">offers ingenious answers\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.ijrte.org\u002Fwp-content\u002Fuploads\u002Fpapers\u002Fv10i1\u002FA57440510121.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">Blockchain-based identification of each box\u003C\u002Fa> provides a secure, immutable ledger for tracking the provenance and movement of pharmaceutical products, ensuring traceability from production to patient delivery​. But we’ve seen other creative ideas, such as printing \u003Ca href=\"https:\u002F\u002Fwww.futurity.org\u002Fcounterfeit-medications-fake-drugs-cyberphysical-watermarks-2711322\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">tiny, edible, all-protein unique watermarks\u003C\u002Fa> on individual pills.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Investing in digital therapeutics\u003C\u002Fh3>\n\n\n\n\u003Cp>Pharmaceutical companies are increasingly recognizing the potential of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-new-buzz-these-are-the-top-examples-of-digital-therapeutics\u002F\">digital therapeutics (DTx)\u003C\u002Fa> as a \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdrugs-vs-digital-therapeutics-a-symbiotic-rivalry\u002F\">complement to traditional medications\u003C\u002Fa>. DTx are evidence-based software applications designed to prevent, manage, or treat medical conditions. They offer a personalised, scalable, and accessible approach to healthcare, and pharma companies are investing heavily in this emerging field.\u003C\u002Fp>\n\n\n\n\u003Cp>Roche, for instance, was an early adopter by \u003Ca href=\"https:\u002F\u002Fwww.mobihealthnews.com\u002Fcontent\u002Froche-acquires-mysugr-new-core-its-digital-diabetes-management-efforts\">acquiring mySugr\u003C\u002Fa>, a leading diabetes management app, to enhance its portfolio of digital solutions for patients with diabetes. Similarly, \u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Findustries\u002Flife-sciences\u002Four-insights\u002Fdigital-therapeutics-preparing-for-takeoff\">GSK partnered with Propeller Health\u003C\u002Fa>, a digital therapeutics company specializing in respiratory diseases, to develop and commercialise digital solutions for patients with asthma and COPD. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Launching (and sometimes closing) digital health units\u003C\u002Fh3>\n\n\n\n\u003Cp>“If you’re not in, you’re out” best describes the sentiment most pharma companies have about the digital health revolution. Many market players decided to establish dedicated units focused on developing and commercialising digital solutions. \u003C\u002Fp>\n\n\n\n\u003Cp>Bayer, for instance, \u003Ca href=\"https:\u002F\u002Fwww.bayer.com\u002Fmedia\u002Fen-us\u002Fbayer-launches-unit-to-develop-new-precision-health-consumer-products\u002F\">launched a new unit\u003C\u002Fa> to develop precision health consumer products, while AstraZeneca \u003Ca href=\"https:\u002F\u002Fwww.bloomberg.com\u002Fnews\u002Farticles\u002F2023-11-20\u002Fastrazeneca-starts-health-tech-business-to-add-ai-to-pharma\">started a health tech business\u003C\u002Fa> to integrate AI into its pharmaceutical offerings. \u003C\u002Fp>\n\n\n\n\u003Cp>However, not all ventures are successful, and some companies have even closed down their digital health units. Biogen, for example, \u003Ca href=\"https:\u002F\u002Fpharmaphorum.com\u002Fnews\u002Fbiogen-shuts-digital-health-unit-and-exits-apple-alliance\">recently shut down its digital health unit\u003C\u002Fa> and ended its collaboration with Apple on a digital health app for Parkinson’s disease.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Let’s see the future! \u003C\u002Fh2>\n\n\n\n\u003Cp>All the trends we’ve discussed so far are already here, happening around us, even if the transformation might be slow or almost invisible in some cases. As progress won’t stop, we can also pinpoint a few advancements that are not yet here, but will surely arrive in the next few years. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">In-silico trials and artificial patients\u003C\u002Fh3>\n\n\n\n\u003Cp>Imagine a world where clinical trials don’t involve recruiting thousands of patients, don’t take years to finish, and don’t cost billions of dollars. This is \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fin-silico-trials-are-the-future\u002F\">the promise of in silico trials\u003C\u002Fa>, where digital representations of human biology are used to test the safety and efficacy of new drugs. While still in its early stages, in silico trials also have the potential to help identify potential safety concerns earlier in the process, potentially sparing patients from unnecessary risks.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-768x432.png\" alt=\"TMF, health data, trial \" class=\"wp-image-24937\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-512x288.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>As we mentioned in the first segment of the article, we see the first studies, but we are not yet capable of actually executing trials this way. Significant challenges remain, including the need for more sophisticated models of human biology and regulatory acceptance. \u003C\u002Fp>\n\n\n\n\u003Cp>Despite these hurdles, in silico trials represent a tantalizing glimpse into the future of drug development, where virtual simulations could complement or even replace traditional clinical trials.\u003C\u002Fp>\n\n\n\n\u003Cp>Another interesting and futuristic concept related to the topic is the idea of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-clinical-trials-artificial-patients-synthetic-data-and-real-time-analysis\u002F\">artificial patients\u003C\u002Fa>. (An artificial patient is a set of data representing the desired human characteristics the best possible way that is based on large amounts of real patient data, without actually including any backtracable real-patient data.) \u003C\u002Fp>\n\n\n\n\u003Cp>One day, virtual patients might become the go-to tools for estimating efficiency and potential side effects of \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC7577280\u002F\">promising drug molecules\u003C\u002Fa> or \u003Ca href=\"https:\u002F\u002Fbiblio.ugent.be\u002Fpublication\u002F8711822\u002Ffile\u002F8711823.pdf\">optimising the use of existing ones\u003C\u002Fa>, to model the success rate of \u003Ca href=\"https:\u002F\u002Fwww.mdpi.com\u002F2077-0375\u002F12\u002F6\u002F548\">future medical devices\u003C\u002Fa> or \u003Ca href=\"https:\u002F\u002Fwww.medgadget.com\u002F2021\u002F06\u002Fin-silico-clinical-trial-replicates-results-of-traditional-trial.html\">treatment methods\u003C\u002Fa>, or, as the latest,\u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2022\u002F4\u002F28\u002F23044586\u002Fvr-chronic-pain-synthetic-clinical-trial-data\"> they can substitute the placebo control group\u003C\u002Fa> for clinical trials. \u003C\u002Fp>\n\n\n\n\u003Cp>As many hope, one day artificial patients may be able to completely substitute humans and animals in clinical trials, most likely with animals being the first. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Leaving digital transformation behind\u003C\u002Fh3>\n\n\n\n\u003Cp>The phrase “digital transformation” has been a buzzword in the pharmaceutical industry for years. However, as digital technologies become increasingly integrated into every aspect of pharma operations, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fpharma-companies-and-digital-transformation\u002F\">we may be entering a post-digital transformation era\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>In this new era, digital tools and technologies are no longer seen as separate initiatives, but as fundamental components of the pharmaceutical landscape. AI, machine learning, and data analytics will be seamlessly woven into drug discovery, clinical trials, marketing, and patient engagement.\u003C\u002Fp>\n\n\n\n\u003Cp>Pharmaceutical companies that thrive in this post-digital era will be those with a mindset where technology is not just a tool, but a catalyst for innovation and transformation. This will require a fundamental shift in culture, processes, and organisational structures. It will also require a willingness to experiment, take risks, and continuously adapt to the ever-evolving digital landscape.\u003C\u002Fp>\n\n\n\n\u003Cp>In the pharma-future, digital technologies can’t be just add-ons, but the foundation of delivering value to patients.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">3D Printing Drugs\u003C\u002Fh3>\n\n\n\n\u003Cp>The technology for \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffuture-3d-printing-drugs-pharmacies-closer-think\u002F\">3D printing drugs is at an exciting stage\u003C\u002Fa> of development, with several approved drugs and ongoing trials. Aprecia Pharmaceuticals’ Spritam, approved by the FDA in 2015, was the first 3D-printed drug designed for epilepsy patients. \u003C\u002Fp>\n\n\n\n\u003Cp>FabRx, a UK-based biotech company, is \u003Ca href=\"https:\u002F\u002F3dprinting.com\u002Fnews\u002Ffirst-3d-printed-pediatric-medicine-trials-to-begin-in-europe\u002F\">conducting the first pediatric clinical trial\u003C\u002Fa> of 3D-printed medicines in Europe, to explore the efficacy and customization of 3D-printed medications in real-world healthcare environments. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1527\" height=\"859\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002F3d_printed_drugs_poster-edited.png\" alt=\"\" class=\"wp-image-36297\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002F3d_printed_drugs_poster-edited.png 1527w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002F3d_printed_drugs_poster-edited-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F09\u002F3d_printed_drugs_poster-edited-768x432.png 768w\" sizes=\"auto, (max-width: 1527px) 100vw, 1527px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>While the technology is still nascent, the potential of 3D-printed drugs to transform the pharmaceutical landscape is undeniable. If pharmacies could print customised pills tailored to an individual’s specific needs, taking into account their age, weight, metabolism, and even genetic profile, this could revolutionise medication adherence and efficacy, as patients receive precisely the right dose in a form that’s easiest for them to take.\u003C\u002Fp>\n\n\n\n\u003Cp>Moreover, 3D printing could enable decentralised drug manufacturing, allowing medications to be produced closer to the point of care, potentially reducing costs and improving access in remote or underserved areas. While regulatory and safety hurdles remain, 3Dp-rinted drugs represent a futuristic trend with the potential to make personalised medicine a reality for millions of patients worldwide.\u003C\u002Fp>\n\n\n\n\u003Cp>The Medical Futurist team keeps a close watch on the news of technologies and innovation in the pharma sector, reporting on all significant developments across our social media channels and providing in-depth analysis right here on our website.\u003C\u002Fp>\n",{"rendered":1189,"protected":16},"\u003Cp>Let’s see six existing and three future trends that will determining the AI and digital health future of the pharma industry. \u003C\u002Fp>\n",33877,{"_acf_changed":16,"footnotes":74},[78,5,250],[1194,85,1195,1196,1197,1198],7969,356,568,1530,7967,[92],[],[1202,637,1203,97,257,1204,1205,1206,1207,1208,96,256],1623,1635,2133,4485,5139,1599,6067,[1210,63,103,104,105,106,107,108,109,260,1211,115,1212,1213,1214,1215,121],"post-56571","tag-drug-repurposing","tag-pharma-2","tag-drug-development","tag-drug-design","tag-ai-in-pharma",{"id":1190,"alt_text":1217,"caption":74,"description":74,"media_type":124,"media_details":1218,"post":1235,"source_url":1236},"TMF, drug, pharma",{"width":126,"height":127,"file":1219,"sizes":1220,"image_meta":1234},"2021\u002F04\u002Ftmf_article_258-01.png",{"medium":1221,"large":1224,"thumbnail":1227,"medium_large":1230,"1536x1536":1231},{"file":1222,"width":133,"height":134,"mime-type":135,"source_url":1223},"tmf_article_258-01-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F04\u002Ftmf_article_258-01-370x208.png",{"file":1225,"width":140,"height":141,"mime-type":135,"source_url":1226},"tmf_article_258-01-768x432.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F04\u002Ftmf_article_258-01-768x432.png",{"file":1228,"width":146,"height":146,"mime-type":135,"source_url":1229},"tmf_article_258-01-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F04\u002Ftmf_article_258-01-150x150.png",{"file":1225,"width":140,"height":141,"mime-type":135,"source_url":1226},{"file":1232,"width":152,"height":153,"mime-type":135,"source_url":1233},"tmf_article_258-01-1536x864.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F04\u002Ftmf_article_258-01-1536x864.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},33827,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F04\u002Ftmf_article_258-01.png",{"cta_type":166,"cta_color":74,"related_posts_footer":1238,"related_posts":16,"related_books":1242,"subtitle":74,"key_takeaways":1244},[1239,1240,1241],56489,56371,56453,[1243,168,1117],24764,[1245,1247,1249],{"title":1246},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">The digital health and AI revolutions are rewriting the rules of pharma.\u003C\u002Fspan>\u003C\u002Fp>\n",{"title":1248},"\u003Cp>Some future trends are crystal clear, others remain almost invisible for now.\u003C\u002Fp>\n",{"title":1250},"\u003Cp>Success in this evolving landscape will require a willingness to experiment, take risks, and continuously adapt to digital advancements.\u003C\u002Fp>\n",{"yoast_wpseo_title":1185,"yoast_wpseo_metadesc":1252,"yoast_wpseo_canonical":1183},"Let's see six existing and three future trends that will determining the AI and digital health future of the pharma industry.",{"self":1254,"collection":1259,"about":1261,"author":1263,"replies":1265,"version-history":1268,"predecessor-version":1272,"wp:featuredmedia":1276,"wp:attachment":1279,"wp:term":1282,"curies":1293},[1255],{"href":1256,"targetHints":1257},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F56571",{"allow":1258},[37],[1260],{"href":189},[1262],{"href":192},[1264],{"embeddable":51,"href":195},[1266],{"embeddable":51,"href":1267},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=56571",[1269],{"count":1270,"href":1271},19,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F56571\u002Frevisions",[1273],{"id":1274,"href":1275},60693,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F56571\u002Frevisions\u002F60693",[1277],{"embeddable":51,"href":1278},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F33877",[1280],{"href":1281},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=56571",[1283,1285,1287,1289,1291],{"taxonomy":11,"embeddable":51,"href":1284},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=56571",{"taxonomy":217,"embeddable":51,"href":1286},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=56571",{"taxonomy":220,"embeddable":51,"href":1288},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=56571",{"taxonomy":223,"embeddable":51,"href":1290},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=56571",{"taxonomy":226,"embeddable":51,"href":1292},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=56571",[1294],{"name":49,"href":50,"templated":51},{"id":1296,"date":1297,"date_gmt":1298,"guid":1299,"modified":1301,"modified_gmt":1302,"slug":1303,"status":62,"type":63,"link":1304,"title":1305,"content":1307,"excerpt":1309,"author":246,"featured_media":1311,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1312,"categories":1313,"tags":1318,"project_category":1327,"contact_email_category":1328,"yst_prominent_words":1329,"class_list":1337,"better_featured_image":1351,"acf":1368,"yoast_meta":1379,"_links":1381},47227,"2026-04-30T10:23:02","2026-04-30T08:23:02",{"rendered":1300},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=47227&_wpnonce=2100cd11c6&status=auto-draft&type=post","2026-04-30T10:23:05","2026-04-30T08:23:05","5-trends-that-will-determine-the-hospital-from-the-future","https:\u002F\u002Fmedicalfuturist.com\u002F5-trends-that-will-determine-the-hospital-from-the-future",{"rendered":1306},"5 Trends That Will Determine The Hospital From The Future",{"rendered":1308,"protected":16},"\n\u003Cp>For centuries, scientists have been trying to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC402202\u002F\" target=\"_blank\">envision the future of hospitals\u003C\u002Fa>. Following the recent shift towards digital health technologies and the adoption of remote care approaches, it is only natural to wonder how these developments will impact those healthcare institutions. What can we expect from them in the future? Will there be hospitals altogether in a decade?\u003C\u002Fp>\n\n\n\n\u003Cp>The short answer is yes, physical institutions will still be part of the future of healthcare. However, their roles will be significantly different from what they currently are. They will integrate new elements of design, accommodate digital health technologies, and become specialised centers for invasive procedures, acute care, and disease prevention. In tandem, a significant portion of care will be offloaded outside of the confines of hospitals and healthcare professionals will need to adopt new roles for this purpose.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"ebook-block-spacer\">\u003C\u002Fdiv>\n\u003Cdiv class=\"ebook-block-backdrop backdrop-blur\" id=\"modal-backdrop-ebook-block_b71c4ea3bbeb3c251b3f291533686a79\">\u003C\u002Fdiv>\n\u003Cinput style=\"display: none\" id=\"modal-ebook-block_b71c4ea3bbeb3c251b3f291533686a79\"\n       value=\"{"featured":{"ID":47427,"post_author":"6","post_date":"2022-09-29 09:59:00","post_date_gmt":"2022-09-29 07:59:00","post_content":"<!-- wp:paragraph -->\\n<p>Learn how hospitals of the future will be designed, and what technologies will be used in hospitals to change the healthcare experience for all.<\\\u002Fp>\\n<!-- \\\u002Fwp:paragraph -->","post_title":"A Guide To The Future Of Hospitals - The Medical Futurist","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"a-guide-to-the-future-of-hospitals","to_ping":"","pinged":"","post_modified":"2023-03-12 18:17:06","post_modified_gmt":"2023-03-12 17:17:06","post_content_filtered":"","post_parent":0,"guid":"https:\\\u002F\\\u002Fapi.medicalfuturist.com\\\u002F?post_type=book&p=47427","menu_order":5,"post_type":"book","post_mime_type":"","comment_count":"0","filter":"raw","featured_image":["https:\\\u002F\\\u002Fcdn.medicalfuturist.com\\\u002Fwp-content\\\u002Fuploads\\\u002F2022\\\u002F09\\\u002Fguide-to-the-future-of-hospitals.png",320,414,false],"leanpub_url":"https:\\\u002F\\\u002Fleanpub.com\\\u002Ffuture-of-hospitals","preview":[{"image":"https:\\\u002F\\\u002Fcdn.medicalfuturist.com\\\u002Fwp-content\\\u002Fuploads\\\u002F2022\\\u002F09\\\u002F0926_Future_of_Hospitals_Cover.png"}],"buy_button_text":"Get it on Leanpub"},"others":[]}\"\u002F>\n\u003Cdiv id=\"ebook-block_b71c4ea3bbeb3c251b3f291533686a79\" class=\"ebook\">\n    \u003Cdiv class=\"ebook-block h-100\">\n        \u003Cdiv class=\"container h-100\">\n            \u003Cdiv class=\"article-body h-100\">\n                \u003Cdiv class=\"row h-100 align-items-center\">\n                    \u003Cdiv class=\"col-md-5 pr-md-5 mb-4 mb-md-0\">\n                        \u003Cimg decoding=\"async\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fguide-to-the-future-of-hospitals.png\" alt=\"\" class=\"img-fluid\">\n                    \u003C\u002Fdiv>\n                    \u003Cdiv class=\"col-md-7 pl-md-3\">\n                        \u003Ch3>A Guide To The Future Of Hospitals – The Medical Futurist\u003C\u002Fh3>\n                        \u003C!-- wp:paragraph -->\n\u003Cp>Learn how hospitals of the future will be designed, and what technologies will be used in hospitals to change the healthcare experience for all.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->                        \u003Cbutton data-target=\"modal-ebook-block_b71c4ea3bbeb3c251b3f291533686a79\"\n                                class=\"ebook-block-button btn btn-lg font-weight-bold btn-tmf-blue mt-3\">\n                            Start Reading Now\n                        \u003C\u002Fbutton>\n                    \u003C\u002Fdiv>\n                \u003C\u002Fdiv>\n            \u003C\u002Fdiv>\n        \u003C\u002Fdiv>\n    \u003C\u002Fdiv>\n\u003C\u002Fdiv>\n\n\n\n\u003Cp>To dive into the trends shaping up this future and the required elements for hospitals to be future-ready, The Medical Futurist updated \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fleanpub.com\u002Ffuture-of-hospitals\u002F\" target=\"_blank\">our beloved e-book ‘A Guide To The Future Of Hospitals\u003C\u002Fa>‘. Composed of seven chapters and including input from industry experts, this e-book aims to equip policymakers, healthcare professionals, and digital health businesses with adequate insights to prepare for the future of hospitals.\u003C\u002Fp>\n\n\n\n\u003Cp>To provide a glimpse of what to expect from our new publication, this article explores five trends that will help shape the hospital of the future. We go into more details in our e-book and we would encourage you to discover more by purchasing a copy of The Guide To The Future Of Hospitals.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>1. The shift of the POC towards homes\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The point-of-care (POC) refers to the location where care is delivered. Traditionally, this referred to the patient’s bedside in a healthcare facility. But as recent years have highlighted, the POC extends beyond hospital walls to include where the patients are, thanks to remote care and telehealth services, wearables, portable diagnostics, and at-home lab tests.\u003C\u002Fp>\n\n\n\n\u003Cp>This means that patients often can now be monitored and receive healthcare recommendations from the comfort of their homes. This has spurred the new concept of ‘\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwelcome-to-the-virtual-ward\" target=\"_blank\">virtual wards\u003C\u002Fa>’.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_277-01-768x432.png\" alt=\"physician shortage moves care from hospitals to the patients' homes\" class=\"wp-image-34881\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_277-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_277-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_277-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_277-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Virtual wards offer hospital-grade attention to patients in their own homes using remote monitoring health tools. These provide real-time monitoring which, combined with two-way communication, allows patients to be in touch with healthcare professionals. The latter can subsequently provide prompt intervention if they identify signs of deterioration. Procedures such as intravenous therapies that require trained professionals are performed by a visiting nurse.\u003C\u002Fp>\n\n\n\n\u003Cp>Such approaches have already been piloted in countries like the \u003Ca href=\"https:\u002F\u002Fwww.england.nhs.uk\u002Fvirtual-wards\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">U.K.\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fvirtual-wards-why-widely-adopted-across-us-healthcare-lloyd-price\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">U.S.\u003C\u002Fa>, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.healthcareitnews.com\u002Fnews\u002Fasia\u002Fcovid-19-virtual-ward-helped-singaporean-health-system-save-over-3500-bed-days\" target=\"_blank\">Singapore\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.9news.com.au\u002Fnational\u002Fvirtual-hospital-adelaide-my-home-hospital-for-sa-health\u002Fdc90a123-8d67-4efb-902c-5e9b74df7e01\" target=\"_blank\" rel=\"noreferrer noopener\">Australia\u003C\u002Fa>. As they become more common in the future, hospitals have to be adequately equipped and designed to support such a modality of care delivery.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>2. Designing specific spaces for remote care consultations\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Virtual wards aren’t the only approach that will make use of remote care but a significant proportion of outpatient consultations will also be handled in this manner. McKinsey forecasts that, in the future, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.bloomberg.com\u002Fnews\u002Farticles\u002F2021-02-23\u002Fhow-the-pandemic-is-transforming-hospital-design\" target=\"_blank\">25% of outpatient services\u003C\u002Fa> could be conducted through telemedicine. Such an approach can help diminish the rate of unnecessary visits while improving the patient experience. \u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ftmf_article_250-51-01-768x432.png\" alt=\"Hospital healtcare gap democratise future\" class=\"wp-image-33551\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ftmf_article_250-51-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ftmf_article_250-51-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ftmf_article_250-51-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ftmf_article_250-51-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>To handle the new normal, clinical spaces will need rethinking to accommodate rooms dedicated to virtual consultations and remote care. These will include user-friendly sound and lighting control, with dual screens to simultaneously converse with the patient and access their medical records,” Dr Diana Anderson \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-hospital-design-inside-the-point-of-care\u002F\">told The Medica\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-hospital-design-inside-the-point-of-care\u002F\" target=\"_blank\">l\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-hospital-design-inside-the-point-of-care\u002F\" target=\"_blank\" rel=\"noreferrer noopener\"> Futurist\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>3. From hand-written notes to voice-to-text\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Clinical documentation systems \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-evolution-of-clinical-documentation-from-paper-to-ai\" target=\"_blank\">evolved significantly during the past decades\u003C\u002Fa>, moving from paper to computers. While most hospitals currently rely on electronic health record (EHR) systems, the necessary administration is among the top contributors to physician burnout. Healthcare professionals spend \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.beckershospitalreview.com\u002Fehrs\u002F6-stats-on-ehr-related-physician-burnout-and-7-tips-to-combat-it.html\" target=\"_blank\">a considerable amount of time\u003C\u002Fa> entering data into EHRs, leaving them with less time to spend with their patients. Many consider EHRs as their \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fvoice-to-text-technologies-shape-the-future\u002F\" target=\"_blank\">number one challenge\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>A promising alternative to manually inputting data into EHRs is voice-to-text technology. It operates via a voice recognition system that transcribes patient-doctor visits without requiring physical input.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif\" alt=\"voice to text technologies help future hospitals to operate more efficiently \" class=\"wp-image-24827\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-370x208.gif 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-1536x864.gif 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-2048x1152.gif 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-512x288.gif 512w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>This field has been developing steadily for decades, but progress has become very evident in the past few years. \u003Ca href=\"https:\u002F\u002Fwww.nuance.com\u002Fen-gb\u002Fhealthcare\u002Fphysician-and-clinical-speech\u002Fdragon-medical.html\">Nuance\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.3m.com\u002F3M\u002Fen_US\u002Fhealth-information-systems-us\u002Fcreate-time-to-care\u002Fclinician-solutions\u002Fspeech-recognition\u002Ffluency-direct\u002F\">3M\u003C\u002Fa> were among the first to focus significant efforts on the automated (medical) scribe segment, offering voice recognition services that create clinical notes that integrate into EHRs.\u003C\u002Fp>\n\n\n\n\u003Cp>Microsoft’s $16bn acquisition of Nuance in 2022 shows new levels of commitment, resources, and partnerships. Following the\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.modernhealthcare.com\u002Fdigital-health\u002Fhimss-2023-epic-microsoft-bring-openais-gpt-4-ehrs\" target=\"_blank\"> early 2023 announcements\u003C\u002Fa> of working on integrating GPT-4 into Epic’s EHR systems, Nuance’s artificial intelligence (AI) based \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.healthcareitnews.com\u002Fnews\u002Fnuance-ai-copilot-now-fully-embedded-epic-ehr\" target=\"_blank\">DAX CoPilot is now fully embedded\u003C\u002Fa> in Epic EHR, and is available to hundreds of hospitals and health systems. \u003C\u002Fp>\n\n\n\n\u003Cp>But Nuance’s DAX (and Dragon) are not the only ones offering AI scribes for medical purposes. A French contender, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.patreon.com\u002Fposts\u002Fnabla-copilot-4-82088198\" target=\"_blank\">Nabla Copilot\u003C\u002Fa> is also successful \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.hcinnovationgroup.com\u002Fanalytics-ai\u002Farticle\u002F53098833\u002Fchildrens-hospital-los-angeles-to-roll-out-nabla-copilot-ambient-ai-assistant\" target=\"_blank\">on the other side of the Atlantic\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>By slashing the need to type into EHRs, physicians can spend more time with their patients and provide medical attention.\u003C\u002Fp>\n\n\n\n\u003Cp>The healthcare sector shifted from paper records to administrators, electronic medical records, and now, voice-to-text applications. But it is not the end of the road. We are looking forward to the potential of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-it-is-important-to-understand-multimodal-large-language-models-in-healthcare\u002F\" target=\"_blank\">Multimodal Large Language Models\u003C\u002Fa> (M-LLMs) which promise a comprehensive and efficient system, potentially reclaiming the human touch in medical care.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>4. AI in decision-making\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Another technology with major potential to enhance the functioning of hospitals is artificial intelligence (AI). Its contribution ranges from reducing \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fambient-intelligence-and-emotion-ai-in-healthcare\u002F\" target=\"_blank\">alarm fatigue\u003C\u002Fa> to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftop-12-health-chatbots\u002F\" target=\"_blank\">triaging\u003C\u002Fa>, from administration to clinical decision-making. \u003C\u002Fp>\n\n\n\n\u003Cp>AI can indeed assist in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-has-a-i-in-medicine-ever-done-for-us\" target=\"_blank\">a multitude of diagnostic processes\u003C\u002Fa>. Such software can, for instance, provide pointers from medical data to help clinicians identify conditions such as \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F23361114\u002F\" target=\"_blank\">ADHD\u003C\u002Fa>, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC10731177\u002F#:~:text=AI%20can%20also%20help%20in,periodic%20leg%20movement%20disorders%2C%20etc.\" target=\"_blank\">sleep disorders\u003C\u002Fa>, and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.mobihealthnews.com\u002Fnews\u002Fzebra-medical-vision-lands-fda-clearance-tool-detect-cardiovascular-disease\" target=\"_blank\">quantify coronary artery calcification\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-768x432.png\" alt=\"things you can and can't expect from A.I. in future hospitals\" class=\"wp-image-30779\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Essentially, AI-powered tools can become the doctor’s new assistant that can crunch through volumes of data from their EHRs and \u003Ca href=\"https:\u002F\u002Fwww.lunduniversity.lu.se\u002Farticle\u002Fai-supported-mammography-screening-found-be-safe\" target=\"_blank\" rel=\"noreferrer noopener\">radiological scans\u003C\u002Fa>. They can then \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-can-you-use-ai-in-your-healthcare-right-now\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">detect patterns and suspicious signs\u003C\u002Fa>, and provide recommendations. Physicians can subsequently interpret those recommendations and determine the optimal clinical route for the patient.\u003C\u002Fp>\n\n\n\n\u003Cp>One especially exciting aspect of the AI revolution is the field of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fgenerative-ai-explained-its-impact-and-future-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">generative AI\u003C\u002Fa>, and large (\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fusing-chatgpt-offline-the-emergence-of-small-language-models\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">and small\u003C\u002Fa>) language models in particular – a segment that stepped into the spotlight recently. \u003C\u002Fp>\n\n\n\n\u003Cp>Although these “general” large language models were not developed (and approved) for giving medical advice, medical LLMs do exist. One of the most prominent examples is \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\u002F\" target=\"_blank\">Google’s Med-PaLM 2\u003C\u002Fa>. This LLM is \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fsites.research.google\u002Fmed-palm\u002F\" target=\"_blank\">specifically trained on a massive dataset of medical text\u003C\u002Fa>, including research papers, clinical notes, and textbooks. This specialised training allows Med-PaLM 2 to understand complex medical terminology and concepts and \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2305.09617.pdf\" target=\"_blank\">according to this pre-print paper\u003C\u002Fa>, with impressive accuracy. Med-PaLM 2 is not accessible to the general public, but the Mayo Clinic has \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2023\u002F7\u002F8\u002F23788265\u002Fgoogle-med-palm-2-mayo-clinic-chatbot-bard-chatgpt\" target=\"_blank\">reportedly been testing\u003C\u002Fa> the system since 2023.\u003C\u002Fp>\n\n\n\n\u003Cp>This brings us to the next major concept: multimodal large language models, or M-LLMs, we mentioned at the end of the previous segment. M-LLMs \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-it-is-important-to-understand-multimodal-large-language-models-in-healthcare\u002F\" target=\"_blank\">will be crucial in the future of hospital\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-it-is-important-to-understand-multimodal-large-language-models-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">s\u003C\u002Fa>. Multimodal systems can process and interpret multiple types of input data, such as text, images, audio, and video, simultaneously. These M-LLM systems will eventually serve as a central hub for various unimodal AI applications in hospitals, translating between various technologies and humans, allowing a single, easy-to-use interface to control a wide range of applications. \u003C\u002Fp>\n\n\n\n\u003Cp>AI has \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fleanpub.com\u002FArtificialIntelligenceinHealthcare\" target=\"_blank\">a vast amount\u003C\u002Fa> of potential in healthcare and as it becomes integral to care delivery, hospitals should be able to accommodate them. \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcloud-gaming-can-bring-artificial-intelligence-to-the-doctors-office\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Cloud computing infrastructure\u003C\u002Fa> could be such a means to make healthcare facilities AI-ready, but the medical staff should also get acquainted with the technology and \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F10-things-you-can-definitely-expect-from-the-future-of-healthcare-ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">its realistic potential\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>5. Cybersecurity and how hospitals can keep patients’ data safe\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>With the increased digitisation of healthcare, healthcare establishments will need to acknowledge the \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fyour-privacy-in-the-digital-health-era-the-medical-futurists-guide\u002F\" target=\"_blank\">accompanying cybersecurity risks\u003C\u002Fa>. Cyberattacks, which \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.aha.org\u002Faha-center-health-innovation-market-scan\u002F2023-10-10-how-prevent-high-impact-cyberattack\" target=\"_blank\">experienced a rise\u003C\u002Fa> in the past years, can \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fhealthitsecurity.com\u002Fnews\u002Fthe-10-biggest-healthcare-data-breaches-of-2020\" target=\"_blank\">compromise sensitive patient data\u003C\u002Fa> as well as \u003Ca rel=\"noreferrer noopener\" style=\"\" href=\"https:\u002F\u002Fwww.hhs.gov\u002Fblog\u002F2022\u002F02\u002F28\u002Fimproving-cybersecurity-posture-healthcare-2022.html\" target=\"_blank\">force the cancellation\u003C\u002Fa> of crucial services such as surgeries and radiology exams. \u003C\u002Fp>\n\n\n\n\u003Cp>Hospitals should thus set up proper safeguarding protocols and approaches against cybercrimes. They can \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcyberthreats-to-hospitals-2021\u002F\" target=\"_blank\">educate and train staff\u003C\u002Fa> to identify and counter activities of malicious third parties, which often \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.csoonline.com\u002Farticle\u002F3648654\u002Fsocial-engineering-definition-examples-and-techniques.html\" target=\"_blank\">exploit human psychology\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>Regarding the technical aspect, anti-virus and anti-ransomware protection should be employed; and operating systems and software applications should be updated. Outdated software was in fact behind the leading cause of the infamous \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-nhs-ransomware-attack-data-privacy-in-digital-health-part-one\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">WannaCry cyberattack on 61 NHS institutions\u003C\u002Fa> in 2017.\u003C\u002Fp>\n\n\n\n\u003Cp>On top of these cybersecurity concerns, hospitals will need to ensure that patients’ data are transparently handled. As they will increasingly employ AI tools, hospitals will need to use patient data to train the algorithms, often while collaborating with Big Tech companies. However, patients might not be explicitly informed of such uses of their data. The collaboration between Google’s DeepMind AI unit and the Royal Free London NHS Trust \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.medicaldevice-network.com\u002Ffeatures\u002Fdata-privacy-advertising-amazon-and-artificial-intelligence\u002F\" target=\"_blank\">exemplifies this\u003C\u002Fa>. In the latter case, certain healthcare-related details of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftechcrunch.com\u002F2016\u002F05\u002F04\u002Fconcerns-raised-over-broad-scope-of-deepmind-nhs-health-data-sharing-deal\u002F\" target=\"_blank\">some 1.6 million patients\u003C\u002Fa> were shared without properly informing patients of such use.\u003C\u002Fp>\n\n\n\n\u003Cp>While there is essentially no effective AI without patient data to train them on, privacy-focused training methods could be adopted. One such approach is decentralised \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffederated-learning-can-protect-patients-data-in-hospitals\u002F\" target=\"_blank\">federated learning\u003C\u002Fa>, which has been shown to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-020-00323-1\" target=\"_blank\">perform comparably\u003C\u002Fa> to other centralised models to deliver \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.medrxiv.org\u002Fcontent\u002F10.1101\u002F2020.12.22.20245407v1.full\" target=\"_blank\">quality\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.jmir.org\u002F2020\u002F10\u002Fe20891\" target=\"_blank\">reliable\u003C\u002Fa> performance. \u003C\u002Fp>\n\n\n\n\u003Cp>Hospitals will thus need to ensure that patients’ data are handled responsibly and transparently; in particular in order to foster a trusting relationship between patients, hospitals and developers for effective digital health adoption.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"463\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fhealthcare-privacy-768x463.png\" alt=\"healthcare privacy tmf hacker laptop computer data\" class=\"wp-image-47163\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fhealthcare-privacy-768x463.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fhealthcare-privacy-1536x926.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fhealthcare-privacy.png 1792w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>While these five trends indicate how the hospital in the future will operate, many more factors come into play. These range from specific design elements through the impact of tech giants to the new role of healthcare professionals. We provide in-depth analyses regarding how these elements factor in the functioning of the hospital of the future and we invite you to discover them in detail in our e-book \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fleanpub.com\u002Ffuture-of-hospitals\" target=\"_blank\">A Guide To The Future Of Hospitals\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":1310,"protected":16},"\u003Cp>Let’s explore five important trends that will help shape the hospital of the future and how they will transform care!\u003C\u002Fp>\n",47421,{"_acf_changed":16,"footnotes":74},[78,1314,5,1315,350,1316,1317,81],6261,798,499,516,[87,1319,1320,1321,1322,84,1323,1324,86,1325,365,1326],7639,543,4471,609,4925,637,723,6743,[1077,92,371,93],[],[1330,1331,1332,1333,96,380,637,1334,754,954,1335,384,1336],2125,2339,2605,2611,4449,1721,1807,[1338,63,103,104,105,106,107,108,1339,109,1340,388,1341,1342,112,117,1343,1344,1345,1346,114,1347,1348,116,1349,402,1350,1085,121,407,122],"post-47227","category-forecast","category-digital-health-research","category-healthcare-design","category-medical-education","tag-future-hospitals","tag-future-of-hospital","tag-remote-care","tag-healthcare-design","tag-point-of-care","tag-telehealth","tag-telemedicine","tag-hospitals",{"id":1311,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":1352,"post":1296,"source_url":1367},{"width":1353,"height":265,"file":1354,"sizes":1355,"image_meta":1366},1280,"2022\u002F09\u002FFuture_of_Hospitals_Header_tmf.png",{"medium":1356,"large":1359,"thumbnail":1362,"medium_large":1365},{"file":1357,"width":133,"height":134,"mime-type":135,"source_url":1358},"Future_of_Hospitals_Header_tmf-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002FFuture_of_Hospitals_Header_tmf-370x208.png",{"file":1360,"width":140,"height":141,"mime-type":135,"source_url":1361},"Future_of_Hospitals_Header_tmf-768x432.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002FFuture_of_Hospitals_Header_tmf-768x432.png",{"file":1363,"width":146,"height":146,"mime-type":135,"source_url":1364},"Future_of_Hospitals_Header_tmf-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002FFuture_of_Hospitals_Header_tmf-150x150.png",{"file":1360,"width":140,"height":141,"mime-type":135,"source_url":1361},{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002FFuture_of_Hospitals_Header_tmf.png",{"cta_type":166,"cta_color":74,"subtitle":74,"related_books":1369,"related_posts_footer":1370,"related_posts":16,"key_takeaways":1374},[997,456,998],[1371,1372,1373],55367,55033,55227,[1375,1377],{"title":1376},"\u003Cp>We will have hospitals in 2040 too, but their roles will be different.\u003C\u002Fp>\n",{"title":1378},"\u003Cp>Parallel to this transformation, the roles of healthcare personnel will also be different with AI, remote care transforming diagnostics and patient-doctor interactions.\u003C\u002Fp>\n",{"yoast_wpseo_title":1306,"yoast_wpseo_metadesc":1380,"yoast_wpseo_canonical":1304},"Let's explore five important trends that shape the hospital of the future and how they transform care and the role of patients and medical professionals!",{"self":1382,"collection":1387,"about":1389,"author":1391,"replies":1393,"version-history":1396,"predecessor-version":1400,"wp:featuredmedia":1404,"wp:attachment":1407,"wp:term":1410,"curies":1421},[1383],{"href":1384,"targetHints":1385},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47227",{"allow":1386},[37],[1388],{"href":189},[1390],{"href":192},[1392],{"embeddable":51,"href":300},[1394],{"embeddable":51,"href":1395},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=47227",[1397],{"count":1398,"href":1399},34,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47227\u002Frevisions",[1401],{"id":1402,"href":1403},60691,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47227\u002Frevisions\u002F60691",[1405],{"embeddable":51,"href":1406},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F47421",[1408],{"href":1409},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=47227",[1411,1413,1415,1417,1419],{"taxonomy":11,"embeddable":51,"href":1412},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=47227",{"taxonomy":217,"embeddable":51,"href":1414},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=47227",{"taxonomy":220,"embeddable":51,"href":1416},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=47227",{"taxonomy":223,"embeddable":51,"href":1418},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=47227",{"taxonomy":226,"embeddable":51,"href":1420},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=47227",[1422],{"name":49,"href":50,"templated":51},{"id":1424,"date":1425,"date_gmt":1426,"guid":1427,"modified":1429,"modified_gmt":1430,"slug":1431,"status":62,"type":63,"link":1432,"title":1433,"content":1435,"excerpt":1437,"author":71,"featured_media":1439,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1440,"categories":1441,"tags":1442,"project_category":1443,"contact_email_category":1444,"yst_prominent_words":1445,"class_list":1447,"better_featured_image":1449,"acf":1479,"yoast_meta":1487,"_links":1489},55303,"2026-04-30T10:22:12","2026-04-30T08:22:12",{"rendered":1428},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=55303&_wpnonce=f90f347a6c&status=auto-draft&type=post","2026-04-30T10:22:13","2026-04-30T08:22:13","10-things-you-can-definitely-expect-from-the-future-of-healthcare-ai","https:\u002F\u002Fmedicalfuturist.com\u002F10-things-you-can-definitely-expect-from-the-future-of-healthcare-ai",{"rendered":1434},"10 Things You Can Definitely Expect From The Future Of Healthcare AI",{"rendered":1436,"protected":16},"\n\u003Cp>The steady cadence of a heart monitor. The anxious wait for test results. These define a patient’s experience, but for healthcare professionals, they are also points of friction. Missed information, redundant diagnostics, or the struggle to make time for true connection… these burdens hinder the most skilled and compassionate providers. \u003C\u002Fp>\n\n\n\n\u003Cp>Artificial intelligence promises material changes on both sides of the stethoscope. By streamlining processes, pinpointing insights, and augmenting decision-making, AI won’t just change how care is delivered – it will reshape the very experience of both giving and receiving that care.\u003C\u002Fp>\n\n\n\n\u003Cp>We have written so much about various details of this revolution in the past period, so it was time to come up with a high-level overview of what we can certainly expect from AI in medicine. We have 10 predictions, coming from four distinct facets of the healthcare spectrum. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The ultimate interface to AI\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>1) The future of large language models (LLMs) is multimodal\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Healthcare isn’t one-dimensional. Physicians synthesize information from conversations, scans, lab results, and a patient’s gestures to reach a diagnosis. Until now, AI has largely worked in silos – analysing text, interpreting images, and so on. To use a simple analogy: current LLMs are like individual tools in a toolbox— a hammer is great for nails, a saw for wood, etc. But a good builder needs to use them in combination. \u003C\u002Fp>\n\n\n\n\u003Cp>Medicine demands this multifaceted approach. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.jmir.org\u002F2023\u002F1\u002Fe52865\" target=\"_blank\">Multimodal AI\u003C\u002Fa> is about giving the algorithm a whole toolbox, not just a single tool. The true revolution will come when AI models can mimic the clinician’s multi-pronged approach. We already see \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-it-is-important-to-understand-multimodal-large-language-models-in-healthcare\u002F\" target=\"_blank\">the early stages of this with multimodal LLMs\u003C\u002Fa>, and their impact will only deepen. Imagine an AI partner as multifaceted as the challenges it aims to solve.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>2) Data annotators will be celebrated\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Multimodal AI might usher in futuristic visions, but its foundation is decidedly unglamorous: meticulously labeled data. Think of every X-ray painstakingly annotated with diagnoses, medical conversations transcribed, and the subtle nuances of lab report values precisely defined. This work \u003Ca href=\"http:\u002F\u002Fjmai.amegroups.com\u002Farticle\u002Fview\u002F5208\">is the lifeblood of accurate AI\u003C\u002Fa>, yet it often goes unnoticed and under-appreciated.\u003C\u002Fp>\n\n\n\n\u003Cp>The path to reliably working medical AI is built with a hidden, but crucial workforce: \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdata-annotation\u002F\">data annotators\u003C\u002Fa>. Their meticulous labeling of medical images, conversations, and test results is the unseen foundation upon which accurate AI models are built. In the rush towards futuristic visions, it’s easy to overlook these essential contributors. It’s time to recognize data annotators as vital players in the AI healthcare revolution, ensuring their work is valued and compensated. We must also create systems for recognition and career paths within the field, for without their expertise, even the most sophisticated algorithms will crumble.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">AI’s impact\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>3) AI will not replace physicians or make specialties vanish\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Despite the breathless headlines, the fear that AI will replace doctors \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-reasons-artificial-intelligence-wont-replace-physicians\u002F#\" target=\"_blank\">is very likely unfounded\u003C\u002Fa>. While AI will undoubtedly change how physicians work, it won’t eliminate the need for their expertise, judgement, and human connection. \u003C\u002Fp>\n\n\n\n\u003Cp>Instead of displacement, the future of healthcare lies in intelligent partnerships between humans and algorithms. AI will become a powerful tool, augmenting physicians’ abilities and ultimately improving patient outcomes. Let’s explore why this is a near certainty… While AI excels at pattern recognition and data analysis, it lacks the empathy essential for patient-centered care. Physicians, in contrast, use a non-linear approach, integrating intuition, experience, and a deep understanding of their patients’ unique needs. \u003C\u002Fp>\n\n\n\n\u003Cp>Additionally, complex AI tools will always demand skilled practitioners to interpret their output and ensure responsible application. And as history consistently demonstrates, technological advancement creates new roles and opportunities rather than simply replacing existing ones.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>4) AI will primarily take over repetitive and data-based tasks\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>AI’s most immediate impact in healthcare won’t be stealing doctors’ jobs, but rather stealing away the drudgery. The \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftowards-creativity-in-healthcare-the-impact-of-digital-technologies-on-medical-specialties-in-an-infographic\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">repetitive, data-driven tasks\u003C\u002Fa> that weigh down physicians – from analyzing scans to sifting through medical records – are prime targets for AI automation. This won’t just save time; it will transform the very nature of medical practice as the human role shifts away from the mundane and toward tasks demanding creativity, connection, and complex problem-solving.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh7-us.googleusercontent.com\u002FWtqLQZa8A1f-XJago-MBOKcntxEY3FpdzEp0yAZqkhsIF0H8Ier3BlHx-1ePqZHVHuYka-cqAZpBYqSwKTwLVpii1EWGE4cei5rAGMaThAQU6FLYYrm3wWeNR_XpKX3tgj7sP4cpZw9o7y8FDIda8-Q\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>As research consistently shows, the best outcomes arise from intelligent human-machine collaboration. By taking on the analytical heavy lifting, AI will free physicians to focus on the art of medicine. This means more time for patient interaction, greater space for nuanced diagnoses, and the exploration of novel treatment strategies. While the fear of AI replacement is understandable, the reality is that doctors who embrace AI as a powerful tool stand to elevate both their profession and the care they provide.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>5) AI will find unusual biomedical associations and biomarkers\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>AI is poised to become an invaluable tool for uncovering hidden patterns and connections in the vast landscape of medical data. Like a detective with superhuman perception, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-curious-case-of-a-i-discovering-unusual-associations-in-medicine\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">AI can spot subtle anomalies or correlations\u003C\u002Fa> that elude even the most experienced human physicians. Race prediction from X-rays, or diabetes detection through voice analysis – these are just early examples of AI identifying biomarkers no human anticipated.\u003C\u002Fp>\n\n\n\n\u003Cp>While such discoveries raise valid concerns about bias and explainability, they also signal a revolutionary shift in medical research. Imagine AI uncovering previously unseen risk factors for devastating diseases or pinpointing the subtle markers that predict which patients will best respond to specific therapies. These unusual associations aren’t just AI curiosities; they challenge us to decipher the algorithm’s logic and unlock new frontiers of medical understanding. Medical detective work will have a new aim: to understand how AI finds what it finds, ensuring these groundbreaking insights are used ethically and for the betterment of patient care.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Skills you will need\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>6) You will need a common language with AI to understand its progress – and it’s not coding\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Contrary to popular belief, the language of AI isn’t Python or Java. The true common tongue is anticipation. Understanding how AI algorithms approach problems, anticipate consequences, and learn from their mistakes is essential for doctors seeking to effectively collaborate with these systems.\u003C\u002Fp>\n\n\n\n\u003Cp>Luckily, this doesn’t require coding classes. Activities like chess, go, or even strategy-based video games (like StarCraft) \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-i-learnt-about-a-i-by-playing-1000-hours-of-chess-in-a-year\u002F\" target=\"_blank\">cultivate the same anticipatory mindset\u003C\u002Fa>. They immerse you in worlds where you must analyse complex scenarios, predict multiple moves ahead, and iteratively adapt based on an opponent’s (or an algorithm’s) actions. Physicians who approach AI with this gamer-like problem-solving mentality will be well-positioned to unlock its potential and guide its development in healthcare.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>7) Prompt engineering is the number one tech skill for medical professionals in the generative AI era\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>If anticipation is the language of AI, then let’s see how you can improve your pronunciation – or to put it technically: learn prompt engineering. \u003C\u002Fp>\n\n\n\n\u003Cp>The AI revolution isn’t just about technology – it’s also about \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.jmir.org\u002F2023\u002F1\u002Fe50638\" target=\"_blank\">how we interact with it\u003C\u002Fa>. In the era of generative AI, those who\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fprompt-engineering-11-tips-to-craft-great-chatgpt-prompts\u002F\" target=\"_blank\"> master the art of communication with these algorithms\u003C\u002Fa> will have a distinct advantage. Prompt engineering, the skill of crafting effective prompts that guide AI models, will become an essential tool for physicians seeking to harness AI’s potential in patient care.\u003C\u002Fp>\n\n\n\n\u003Cp>Think of it like this: physicians already ‘prompt’ patients to gain the information needed for diagnosis. With AI, the skill evolves. Mastering prompt engineering will allow doctors to pinpoint the most accurate information, request tailored analyses, and ensure the AI’s output aligns precisely with their patient’s needs. Those who embrace this skillset will not only improve their efficiency but will also unlock the true promise of the human-AI partnership.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Challenges\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>8) We need proper guidelines about health equity and fighting bias\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Bias and lack of equity are among the most urgent challenges as AI transforms healthcare. The good news: \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F4-approaches-to-eliminate-bias-in-healthcare-a-i\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">we’re already seeing efforts\u003C\u002Fa>, from technical toolkits to research frameworks, to tackle these issues head-on. However, translating these solutions into widespread practice requires a foundation of clear, actionable guidelines. Expect a surge in standards focused on data fairness, algorithmic transparency, and the ongoing monitoring of AI systems in real-world settings.\u003C\u002Fp>\n\n\n\n\u003Cp>These guidelines won’t just protect patients; they’ll be essential for building trust and broad acceptance of AI in medicine. Doctors seeking to uphold the principle of ‘do no harm’ in the AI era will need fluency \u003Ca href=\"https:\u002F\u002Fblog.research.google\u002F2024\u002F03\u002Fheal-framework-for-health-equity.html\" target=\"_blank\" rel=\"noreferrer noopener\">in these equity standards\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>9) Adaptive AI and generative AI will get new regulatory categories\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>Generative and adaptive AI pose a thrilling, yet unprecedented \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-current-state-of-fda-approved-ai-based-medical-devices\u002F\" target=\"_blank\">challenge for regulatory bodies\u003C\u002Fa>. Unlike static medical devices or software, these algorithms evolve and continuously learn. This is a brand new challenge: the likes of the FDA never before had to figure out a suitable framework for something that might be different by tomorrow. \u003C\u002Fp>\n\n\n\n\u003Cp>This requires a regulatory approach that balances innovation with patient safety. We expect the emergence of entirely new categories and flexible frameworks specifically designed to govern these dynamic AI systems.\u003C\u002Fp>\n\n\n\n\u003Cp>Healthcare professionals will need to become active participants in shaping these new regulatory standards. Understanding the unique challenges of generative and adaptive AI, as well as engaging in the ethical considerations surrounding their use, will be vital. Only by working in partnership with regulators can healthcare providers ensure a future where AI innovation flourishes while patient well-being remains the guiding principle.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>10) Medicine and healthcare will struggle to adapt and filter deepfakes\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>As deepfake technology becomes more sophisticated, medicine faces a unique vulnerability. Patients could \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-to-spot-if-your-remote-care-physician-is-an-a-i\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">encounter deepfake doctors\u003C\u002Fa>, convincingly mimicking their trusted healthcare providers. Fabricated patient records or misleading research data have the potential to disrupt care and erode trust. Healthcare institutions will struggle to adapt, requiring both healthcare personnel and patients to be educated on the potential threats of deepfakes. Developing robust methods for identifying and combating deepfakes will become a critical priority.\u003C\u002Fp>\n\n\n\n\u003Cp>This is where medical professionals need to be vigilant. We must question the authenticity of information, especially AI-generated content, to foster a culture of skepticism within the field. The trust patients place in healthcare hinges on our ability to discern fact from fiction in an era where the lines are increasingly blurred. Will you have secret passwords with your patients? While it’s too early to predict specific solutions, staying ahead of the deepfake curve is essential to protect both our patients and the integrity of medical knowledge.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The AI healthcare revolution won’t unfold in isolation\u003C\u002Fh2>\n\n\n\n\u003Cp>The future of AI in healthcare is undeniably complex, but it brims with transformative potential. From unlocking hidden biomarkers to streamlining administrative burdens, AI will improve patient care and redefine the role of physicians. However, this revolution won’t unfold on its own. It requires collaboration between physicians, technologists, regulators, and patients. Healthcare professionals need to embrace this change and use their ethical compass to shape the future of medicine for the better.\u003C\u002Fp>\n\n\n\n\u003Cp>While AI promises to augment our abilities, it’s essential to remember that healthcare remains a fundamentally human endeavor. The most sophisticated algorithm can never replace empathy, intuition, or the healing power of the patient-doctor bond. Technology can serve as a powerful tool, empowering us to provide better, more compassionate care for all.\u003C\u002Fp>\n",{"rendered":1438,"protected":16},"\u003Cp>Artificial Intelligence promises material changes on both sides of the stethoscope, but this revolution won’t unfold on its own.\u003C\u002Fp>\n",55315,{"_acf_changed":16,"footnotes":74},[78,5],[84,85,86],[92],[],[639,1446,637,754,954,384,257],2613,[1448,63,103,104,105,106,107,108,109,114,115,116,121],"post-55303",{"id":1439,"alt_text":1450,"caption":74,"description":1450,"media_type":124,"media_details":1451,"post":1424,"source_url":1478},"AI, doctor, screen, diagnosis",{"width":761,"height":762,"file":1452,"filesize":1453,"sizes":1454,"image_meta":1476},"2024\u002F03\u002Ftmf_article_406.png",1871732,{"medium":1455,"large":1459,"thumbnail":1463,"medium_large":1467,"1536x1536":1468,"2048x2048":1472},{"file":1456,"width":418,"height":419,"mime-type":135,"filesize":1457,"source_url":1458},"tmf_article_406-370x208.png",55245,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406-370x208.png",{"file":1460,"width":423,"height":424,"mime-type":135,"filesize":1461,"source_url":1462},"tmf_article_406-768x432.png",147338,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406-768x432.png",{"file":1464,"width":428,"height":428,"mime-type":135,"filesize":1465,"source_url":1466},"tmf_article_406-150x150.png",22077,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406-150x150.png",{"file":1460,"width":423,"height":424,"mime-type":135,"filesize":1461,"source_url":1462},{"file":1469,"width":433,"height":434,"mime-type":135,"filesize":1470,"source_url":1471},"tmf_article_406-1536x864.png",385687,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406-1536x864.png",{"file":1473,"width":669,"height":670,"mime-type":135,"filesize":1474,"source_url":1475},"tmf_article_406-2048x1152.png",582120,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":1477},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_406.png",{"cta_type":166,"cta_color":74,"related_books":16,"related_posts_footer":16,"related_posts":16,"subtitle":74,"key_takeaways":1480},[1481,1483,1485],{"title":1482},"\u003Cp>From unlocking hidden biomarkers to streamlining administrative burdens, AI will improve patient care and redefine the role of physicians.\u003C\u002Fp>\n",{"title":1484},"\u003Cp>Technology can serve as a powerful tool, but healthcare remains a fundamentally human endeavor.\u003C\u002Fp>\n",{"title":1486},"\u003Cp>This technological revolution won’t unfold on its own, it requires collaboration between physicians, technologists, regulators, and patients.\u003C\u002Fp>\n",{"yoast_wpseo_title":1434,"yoast_wpseo_metadesc":1488,"yoast_wpseo_canonical":1432},"Artificial Intelligence promises material changes on both sides of the stethoscope, but this revolution won't unfold on its own.",{"self":1490,"collection":1495,"about":1497,"author":1499,"replies":1501,"version-history":1504,"predecessor-version":1507,"wp:featuredmedia":1511,"wp:attachment":1514,"wp:term":1517,"curies":1528},[1491],{"href":1492,"targetHints":1493},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55303",{"allow":1494},[37],[1496],{"href":189},[1498],{"href":192},[1500],{"embeddable":51,"href":195},[1502],{"embeddable":51,"href":1503},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=55303",[1505],{"count":246,"href":1506},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55303\u002Frevisions",[1508],{"id":1509,"href":1510},58683,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55303\u002Frevisions\u002F58683",[1512],{"embeddable":51,"href":1513},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F55315",[1515],{"href":1516},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=55303",[1518,1520,1522,1524,1526],{"taxonomy":11,"embeddable":51,"href":1519},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=55303",{"taxonomy":217,"embeddable":51,"href":1521},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=55303",{"taxonomy":220,"embeddable":51,"href":1523},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=55303",{"taxonomy":223,"embeddable":51,"href":1525},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=55303",{"taxonomy":226,"embeddable":51,"href":1527},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=55303",[1529],{"name":49,"href":50,"templated":51},{"id":1531,"date":1532,"date_gmt":1533,"guid":1534,"modified":1536,"modified_gmt":1537,"slug":1538,"status":62,"type":63,"link":1539,"title":1540,"content":1542,"excerpt":1544,"author":71,"featured_media":1546,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1547,"categories":1548,"tags":1549,"project_category":1550,"contact_email_category":1551,"yst_prominent_words":1552,"class_list":1554,"better_featured_image":1556,"acf":1583,"yoast_meta":1591,"_links":1593},60627,"2026-04-22T10:42:09","2026-04-22T08:42:09",{"rendered":1535},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60627&_wpnonce=b7bd25a52d&status=auto-draft&type=post","2026-04-22T10:42:10","2026-04-22T08:42:10","new-course-ai-survival-kit-for-medical-professionals","https:\u002F\u002Fmedicalfuturist.com\u002Fnew-course-ai-survival-kit-for-medical-professionals",{"rendered":1541},"New Course: AI Survival Kit For Medical Professionals",{"rendered":1543,"protected":16},"\n\u003Cp>AI has been part of the conversation in healthcare for over a decade, but something has clearly changed. What used to be a promise about the future is now part of everyday clinical reality. AI is already present in how we document, analyze data, and support decision-making. \u003Cstrong>Yet, despite all the headlines and excitement, most medical professionals are still left with a simple and very practical question: what should I actually do with it?\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>The rapid rise of generative AI and large language models has accelerated this shift. With hundreds of millions of users and massive investments from both technology companies and healthcare institutions, AI has become the ultimate conversation starter in medicine. Questions such as whether AI will replace physicians, diagnose patients, or reshape the economics of healthcare are everywhere. However, these questions often remain abstract and do not help clinicians make better decisions in their daily work.\u003C\u002Fp>\n\n\n\n\u003Cp>At the same time, it is not flawless. It can produce misleading outputs, introduce bias, or lead to over-reliance if used incorrectly. This makes it essential to approach AI with the same mindset as any other medical tool: grounded in evidence, aware of limitations, and focused on patient benefit.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>This is why we launched a fast-track course: \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.thinkific.com\u002Fcourses\u002FAI-survival-kit\">AI Survival Kit For Medical Professionals\u003C\u002Fa>!\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"434\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FAI-course-banner-2-768x434.png\" alt=\"\" class=\"wp-image-60631\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FAI-course-banner-2-768x434.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FAI-course-banner-2-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FAI-course-banner-2.png 1500w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">About the course\u003C\u002Fh2>\n\n\n\n\u003Cp>The goal of the course is to cut through the noise and focus on what actually works today. It is a practical, no-hype guide to using AI in everyday clinical work, showing:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>what AI tools you can safely use now\u003C\u002Fli>\n\n\n\n\u003Cli>what you should never delegate to AI\u003C\u002Fli>\n\n\n\n\u003Cli>how to stay in control as a physician\u003C\u002Fli>\n\n\n\n\u003Cli>how to communicate about AI with patients\u003C\u002Fli>\n\n\n\n\u003Cli>how to prepare your career for the changes ahead\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>The course is built around real-world examples and actionable frameworks. It covers areas such as AI-supported documentation, including the use of AI scribes, clinical decision support, patient communication, and prompt engineering. It also addresses critical topics such as evaluating AI tools, understanding their limitations, and maintaining clinical responsibility.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>The curriculum is structured into four main chapters:\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Chapter 1\u003C\u002Fstrong> introduces the course and provides a reality check about the current state of AI in healthcare\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Chapter 2\u003C\u002Fstrong> explores where AI stands today, including case studies, opportunities, risks, and advantages\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Chapter 3\u003C\u002Fstrong> serves as a practical guide to using AI tools, from generative AI and large language models to AI scribes\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Chapter 4\u003C\u002Fstrong> focuses on how your career can be augmented by AI\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Bonus chapter\u003C\u002Fstrong> offers additional insights and resources\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>This course is designed for medical professionals who want practical guidance on how to navigate AI in their daily work, stay relevant, and make informed decisions about using or evaluating AI tools. You do not need any technical background. The focus is on clarity, confidence, and safe application.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>The course is designed as a fast-track program and can be completed in just 1–3 hours\u003C\u002Fstrong>, making it easy to fit into even the busiest clinical schedule. You can go through it in one sitting or break it into shorter sessions over a few days. \u003C\u002Fp>\n\n\n\n\u003Cp>A certificate of completion is provided to students who successfully finish the course. The certificate can be downloaded from the course platform and can serve as evidence of your understanding and knowledge in the field of artificial intelligence in medicine and healthcare.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>AI will not replace physicians, but it will change what it means to be one. Those who ignore it risk falling behind, while those who learn how to use it thoughtfully can shape how it is implemented in healthcare.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.thinkific.com\u002Fcourses\u002FAI-survival-kit\">Check it out to find out how to bring AI into your clinical work today!\u003C\u002Fa>\u003C\u002Fstrong>\u003C\u002Fp>\n",{"rendered":1545,"protected":16},"\u003Cp>AI has been part of the conversation in healthcare for over a decade, but something has clearly changed. What used to be a promise about […]\u003C\u002Fp>\n",60629,{"_acf_changed":16,"footnotes":74},[5],[],[],[],[754,638,1553],5811,[1555,63,103,104,105,106,107,109],"post-60627",{"id":1546,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":1557,"post":1531,"source_url":1582},{"width":1558,"height":1559,"file":1560,"filesize":1561,"sizes":1562,"image_meta":1580},1600,900,"2026\u002F04\u002FTMF-AI-course-2-s.png",1572176,{"medium":1563,"large":1567,"thumbnail":1571,"medium_large":1575,"1536x1536":1576},{"file":1564,"width":418,"height":419,"mime-type":135,"filesize":1565,"source_url":1566},"TMF-AI-course-2-s-370x208.png",88196,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FTMF-AI-course-2-s-370x208.png",{"file":1568,"width":423,"height":424,"mime-type":135,"filesize":1569,"source_url":1570},"TMF-AI-course-2-s-768x432.png",345620,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FTMF-AI-course-2-s-768x432.png",{"file":1572,"width":428,"height":428,"mime-type":135,"filesize":1573,"source_url":1574},"TMF-AI-course-2-s-150x150.png",30663,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FTMF-AI-course-2-s-150x150.png",{"file":1568,"width":423,"height":424,"mime-type":135,"filesize":1569,"source_url":1570},{"file":1577,"width":433,"height":434,"mime-type":135,"filesize":1578,"source_url":1579},"TMF-AI-course-2-s-1536x864.png",1170789,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FTMF-AI-course-2-s-1536x864.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":1581},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002FTMF-AI-course-2-s.png",{"cta_type":74,"cta_color":74,"subtitle":74,"key_takeaways":1584,"related_books":16,"related_posts_footer":16,"related_posts":16},[1585,1587,1589],{"title":1586},"\u003Cp>AI has been part of the conversation in healthcare for over a decade, but something has clearly changed. What used to be a promise about the future is now part of everyday clinical reality.\u003C\u002Fp>\n",{"title":1588},"\u003Cp>This is why we launched a fast-track course: AI Survival Kit For Medical Professionals!\u003C\u002Fp>\n",{"title":1590},"\u003Cp>AI will not replace physicians, but it will change what it means to be one. Those who ignore it risk falling behind, while those who learn how to use it thoughtfully can shape how it is implemented in healthcare.\u003C\u002Fp>\n",{"yoast_wpseo_title":1592,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":1539},"New Course: AI Survival Kit For Medical Professionals - The Medical Futurist",{"self":1594,"collection":1599,"about":1601,"author":1603,"replies":1605,"version-history":1608,"predecessor-version":1611,"wp:featuredmedia":1615,"wp:attachment":1618,"wp:term":1621,"curies":1632},[1595],{"href":1596,"targetHints":1597},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60627",{"allow":1598},[37],[1600],{"href":189},[1602],{"href":192},[1604],{"embeddable":51,"href":195},[1606],{"embeddable":51,"href":1607},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60627",[1609],{"count":905,"href":1610},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60627\u002Frevisions",[1612],{"id":1613,"href":1614},60633,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60627\u002Frevisions\u002F60633",[1616],{"embeddable":51,"href":1617},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60629",[1619],{"href":1620},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60627",[1622,1624,1626,1628,1630],{"taxonomy":11,"embeddable":51,"href":1623},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=60627",{"taxonomy":217,"embeddable":51,"href":1625},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=60627",{"taxonomy":220,"embeddable":51,"href":1627},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=60627",{"taxonomy":223,"embeddable":51,"href":1629},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=60627",{"taxonomy":226,"embeddable":51,"href":1631},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60627",[1633],{"name":49,"href":50,"templated":51},{"id":1371,"date":1635,"date_gmt":1636,"guid":1637,"modified":1639,"modified_gmt":1640,"slug":1641,"status":62,"type":63,"link":1642,"title":1643,"content":1645,"excerpt":1647,"author":71,"featured_media":1649,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1650,"categories":1651,"tags":1652,"project_category":1655,"contact_email_category":1656,"yst_prominent_words":1657,"class_list":1660,"better_featured_image":1664,"acf":1693,"yoast_meta":1699,"_links":1702},"2026-03-30T10:28:57","2026-03-30T08:28:57",{"rendered":1638},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=55367&_wpnonce=671bd616eb&status=auto-draft&type=post","2026-03-30T10:28:58","2026-03-30T08:28:58","technobabble-to-english-a-buzzword-guide-for-medical-ai-and-digital-health","https:\u002F\u002Fmedicalfuturist.com\u002Ftechnobabble-to-english-a-buzzword-guide-for-medical-ai-and-digital-health",{"rendered":1644},"Technobabble To English: A Buzzword Guide For Medical AI And Digital Health",{"rendered":1646,"protected":16},"\n\u003Cp>Navigating AI in medicine and digital health can feel like ordering a coffee at that new hipster café downtown: exciting yet slightly overwhelming with a menu that seems to be in a different language. A while ago \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-digital-health-buzzword-radar\u002F\" target=\"_blank\">we published a buzzword\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-digital-health-buzzword-radar\u002F\" target=\"_blank\" rel=\"noreferrer noopener\"> \u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-digital-health-buzzword-radar\u002F\" target=\"_blank\">dictionary\u003C\u002Fa> to help you decode the most frequently repeated terms. Back then \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fa-physicians-visual-guide-to-artificial-intelligence\u002F\" target=\"_blank\">artificial intelligence\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmachine-learning-and-deep-learning-in-medicine\u002F\" target=\"_blank\">machine learning\u003C\u002Fa> were rarely heard exotic expressions, but as quite a few years have passed, a whole new set of mambo-jambo emerged, waiting to be explained. \u003C\u002Fp>\n\n\n\n\u003Cp>You’re probably sick of hearing the latest digital health buzzwords without any actual context, so let’s translate this technobabble into plain English. Here is our survival guide in the bewildering world of digital health terminology. We’re decoding the lingo, from radiomics and theranostics to LLM and GenAI – ensuring you’re not just nodding along when discussing these topics. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Generative AI, aka GenAI\u003C\u002Fh2>\n\n\n\n\u003Cp>The wunderkind of the past year, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fgenerative-ai-explained-its-impact-and-future-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">generative AI\u003C\u002Fa> goes beyond simple automation, venturing into the world of creation. This term refers to a category of AI algorithms that look for patterns and structures in the sample data and develop new ones. For example, it can simulate discussions and learn how we, people, would be satisfied with the results. But it does it billions of times a day. So it improves at an unbelievable rate. \u003C\u002Fp>\n\n\n\n\u003Cp>Most GenAI algorithms can create a single kind of output, it can be text, image, video, music, code, and the list goes on and on. And some algorithms can also create multiple types, the most accessible of these is the subscription (GPT-4) model of OpenAI’s ChatGPT. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002F0821_generative-ai-cover-01-768x432.png\" alt=\"\" class=\"wp-image-52139\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002F0821_generative-ai-cover-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002F0821_generative-ai-cover-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002F0821_generative-ai-cover-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F08\u002F0821_generative-ai-cover-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The technology is based on algorithms trained on vast datasets, learning patterns, and generating outputs that can sometimes seem indistinguishable from human-generated work. At the moment, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\u002F\" target=\"_blank\">we don’t have widely-used, specifically medically trained models yet\u003C\u002Fa>, but we can glimpse into this future when using such models in our private lives. \u003C\u002Fp>\n\n\n\n\u003Cp>In the context of digital health, its potential goes way beyond automating routine tasks. We can expect future medical generative AI to also generate personalised treatment plans, drug discovery leads, or realistic medical simulations for training purposes. Using future medical generative AI for generating personalised patient education materials to drafting potential chemical compounds for new medications, will be like having a creative assistant at your beck and call. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Large Language Models, aka LLMs\u003C\u002Fh2>\n\n\n\n\u003Cp>Large Language Models (LLMs) are a subset of Generative AI. While the former refers to any AI system that can create or generate new content, LLMs specifically focus on generating and understanding human language and producing human-like text. \u003C\u002Fp>\n\n\n\n\u003Cp>For healthcare purposes, we will need specialised models, developed and approved for clinical use. The closest we have to this goal is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\u002F\" target=\"_blank\">Google’s Med-PaLM 2\u003C\u002Fa>. This LLM is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fsites.research.google\u002Fmed-palm\u002F\" target=\"_blank\">specifically trained on a massive dataset of medical text\u003C\u002Fa>, including research papers, clinical notes, and textbooks. This specialised training allows Med-PaLM 2 to understand complex medical terminology and concepts and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2305.09617.pdf\" target=\"_blank\">according to this pre-print paper\u003C\u002Fa>, with impressive accuracy.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_371-768x432.png\" alt=\"TMF, ChatGPT alternatives\" class=\"wp-image-51297\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_371-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_371-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_371-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Ftmf_article_371.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Med-PaLM 2 is not accessible to the general public, but the Mayo Clinic has \u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2023\u002F7\u002F8\u002F23788265\u002Fgoogle-med-palm-2-mayo-clinic-chatbot-bard-chatgpt\" target=\"_blank\" rel=\"noreferrer noopener\">reportedly been testing\u003C\u002Fa> the system since 2023. In the same year, Google also introduced a \u003Ca href=\"https:\u002F\u002Fcloud.google.com\u002Fblog\u002Ftopics\u002Fhealthcare-life-sciences\u002Fintroducing-medlm-for-the-healthcare-industry\" target=\"_blank\" rel=\"noreferrer noopener\">medicine-specific model called MedLM\u003C\u002Fa>, available to Google Cloud customers in the United States.\u003C\u002Fp>\n\n\n\n\u003Cp>In the future, we’ll have LLMs that can generate detailed summaries, translate medical jargon into patient-friendly explanations, and even draft research papers. While they will not replace your clinical judgement, they will serve as a tireless research assistant who can quickly synthesize evidence on demand. LLMs have the potential to streamline literature reviews, power next-generation clinical decision support tools, and enable more accessible patient communication.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Value-Based Care\u003C\u002Fh2>\n\n\n\n\u003Cp>This concept aims to change the workings of healthcare systems to focus on quality and not quantity. Or, using a profane metaphor: making medicine less like a fast-food chain, serving as many as possible, as quickly as possible, and more like a Michelin-starred restaurant, where the quality of your experience is paramount.\u003C\u002Fp>\n\n\n\n\u003Cp>Value-based care rewrites the “more procedures, more pay” script, and aims to deliver the best possible outcomes for patients at a sustainable cost. In theory, it rewards healthcare providers for keeping their patients healthy, not just for treating them when they’re sick.\u003C\u002Fp>\n\n\n\n\u003Cp>In a value-based system, a doctor gets a bonus for keeping your diabetes under control instead of just billing you for each blood test. It incentivises prevention, better chronic disease management, and overall patient well-being.\u003C\u002Fp>\n\n\n\n\u003Cp>This is a very noble idea, but we have to note it is extremely difficult to consistently measure said value and implement the changes that focus on long-term health outcomes. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Digital Front Door or DFD [Companies]\u003C\u002Fh2>\n\n\n\n\u003Cp>A \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-front-doors-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">“digital front door” company\u003C\u002Fa> is a healthcare technology provider that helps patients access healthcare services through a single, user-friendly platform. These platforms provide a seamless experience for patients, allowing them to schedule appointments, communicate with healthcare providers, access their health records, and even pay their bills. These solutions are transforming the healthcare industry by making it easier for patients to receive care. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_digital_front_door-768x432.jpg\" alt=\"tmf digital front door\" class=\"wp-image-50635\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_digital_front_door-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_digital_front_door-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_digital_front_door-1536x864.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_digital_front_door.jpg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>With virtual care options and the ability to access healthcare services remotely, patients can receive the care they need from the comfort of their own homes. These solutions also help healthcare providers by reducing administrative burdens, streamlining workflows, and improving patient satisfaction.\u003C\u002Fp>\n\n\n\n\u003Cp>DFD solutions are as diverse as the healthcare ecosystem itself, as the best processes vary from provider to provider. Thus the good practices we can currently find on the market are quite unique as well.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Virtual Wards\u003C\u002Fh2>\n\n\n\n\u003Cp>A \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwelcome-to-the-virtual-ward\u002F\" target=\"_blank\">virtual ward\u003C\u002Fa> is a solution that supports patients who would otherwise be in hospital to get acute care, remote monitoring, and treatment in their own homes, with the use of digital, remote monitoring health tools relaying real-time data to the hospital. Virtual wards provide the same data in real-time as would be available if the patient was hospitalised.\u003C\u002Fp>\n\n\n\n\u003Cp>The digital health arsenal used is dependent on the patients’ condition, but generally measures health parameters such as heart rate, blood pressure, body temperature, and blood oxygen level monitoring besides other, condition-specific metrics. The data is displayed in real-time in the hospital, and the support staff follows it as closely as if the patient was monitored in the intensive care unit. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Ftmf_article_308-01-768x432.png\" alt=\"hospital health data connected virtual ward\" class=\"wp-image-37603\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Ftmf_article_308-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Ftmf_article_308-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Ftmf_article_308-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002Ftmf_article_308-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>This is two-way communication. The patient has the option to immediately contact the health team, and real-time data allows healthcare providers to immediately intervene if measurements suggest deterioration in the patient’s condition.\u003C\u002Fp>\n\n\n\n\u003Cp>In this model, everything that physically needs a trained professional, like blood tests, wound dressings, intravenous therapy and so on, is carried out by a visiting nurse.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Virtual First\u003C\u002Fh2>\n\n\n\n\u003Cp>Originating from the tech industry, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-does-virtual-first-mean-in-healthcare\u002F\" target=\"_blank\">“virtual first”\u003C\u002Fa> refers to experiencing a service primarily virtually or remotely rather than through a traditional centralised physical location. This approach gained popularity amidst the COVID-19 pandemic, with \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fedition.cnn.com\u002F2020\u002F10\u002F13\u002Fsuccess\u002Fdropbox-virtual-first-future-of-work\u002Findex.html\" target=\"_blank\">companies like Dropbox\u003C\u002Fa> adopting such an ethos and this trickled into healthcare delivery as well. \u003C\u002Fp>\n\n\n\n\u003Cp>In healthcare, a \u003Ca href=\"https:\u002F\u002Fwww.wheel.com\u002Fcompanies-blog\u002Fwhat-is-virtual-first-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">virtual first approach involves\u003C\u002Fa> accessing medical care first through virtual means, which can then be supplemented by follow-up in-person visits as necessary (for example, to perform radiological scans). This relies on the functionality and interoperability of digital tools such as video conferencing software and personal health sensors for remote data capture.\u003C\u002Fp>\n\n\n\n\u003Cp>This approach can sound similar to other terms such as telehealth, virtual or remote care, but there are some differences. Virtual first healthcare represents \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.wheel.com\u002Fcompanies-blog\u002Fwhat-is-virtual-first-healthcare\" target=\"_blank\">a hybrid model\u003C\u002Fa>. It focuses on the first interaction being virtual and combines it with supplemental in-person services to optimise the care delivery as appropriate.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Imageomics\u003C\u002Fh2>\n\n\n\n\u003Cp>This new science discipline lies at the intersection of medical imaging and big data analytics. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nationalacademies.org\u002Fevent\u002F12-07-2022\u002Fimageomics-a-new-field-of-science-at-the-crossroads-of-biology-and-machine-learning\" target=\"_blank\">Imageonics\u003C\u002Fa> is the Sherlock Holmes of healthcare, deducing vital clues about a patient’s health from medical images. Its goal is to extract information about biology directly from the images. On a broad scale, this field aims to leverage the power of artificial intelligence to analyse patterns and interesting information like the appearance, behavior, and location of species.  \u003C\u002Fp>\n\n\n\n\u003Cp>In healthcare, it aims to extract actionable data and information from medical images, finding hidden patterns and insights that might not be obvious to the human eye. By turning images into actionable insights, we can achieve a more comprehensive understanding, leading to earlier interventions, more precise treatments, and ultimately, better outcomes.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Radiomics\u003C\u002Fh2>\n\n\n\n\u003Cp>Similarly to imageomics, \u003Ca href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRadiomics\" target=\"_blank\" rel=\"noreferrer noopener\">radiomics \u003C\u002Fa>also comes from the advanced intersections of medical imaging and data analysis, but the latter focuses on slightly different aspects and scopes within this field.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-768x432.png\" alt=\"AI, radiomics, radiology, X-ray\" class=\"wp-image-54747\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_399-2048x1152.png 2048w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Radiomics is primarily concerned with extracting a large number of quantitative features from radiological images, such as CT scans, MRI scans, and PET scans. These features, which can include shape, texture, and intensity, are then analysed to detect patterns that could be indicative of certain diseases, the progression of diseases, or the potential response to treatments. Radiomics is particularly focused on the detailed analysis of images to support diagnosis, prognosis, and therapy planning, mostly within the context of oncology (cancer care) but also extending to other diseases.\u003C\u002Fp>\n\n\n\n\u003Cp>While Imageomics holds potential for applications beyond radiology like analysis of pathology slides for disease diagnosis or prediction, or even analysing video data of a patient’s gait for potential neurological conditions, radiomics focuses more on refining cancer diagnosis, predicting tumour aggressiveness, and guiding personalised treatment plans within the realm of radiology.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Theranostics\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.uchicagomedicine.org\u002Fcancer\u002Ftypes-treatments\u002Ftheranostics#:~:text=Theranostics%20is%20a%20two%2Dpronged,specific%20target%20in%20the%20body\" target=\"_blank\">Theranostics \u003C\u002Fa>is a portmanteau of “therapy” and “diagnostics.” This field is revolutionising how we approach diseases, particularly cancer, by combining diagnostic testing with targeted therapy based on the test results. Theranostics works by employing molecular-level information to diagnose conditions accurately and then using that information to guide targeted treatment.\u003C\u002Fp>\n\n\n\n\u003Cp>The process begins with diagnostic tests that identify specific biomarkers or traits of a disease in an individual. Once these markers are known, a tailored therapeutic agent is deployed to target those specific markers. This allows for highly personalised treatment plans that can be more effective, less invasive, and with fewer side effects than traditional one-size-fits-all approaches.\u003C\u002Fp>\n\n\n\n\u003Cp>Theranostics is particularly groundbreaking in the field of oncology, where it’s used to target specific cancer cells based on their unique characteristics. For example, in certain types of cancer, theranostic agents can deliver radioactive substances directly to cancer cells, destroying them from within while sparing healthy tissue. This precision not only improves treatment outcomes but also enhances patients’ quality of life during treatment.\u003C\u002Fp>\n\n\n\n\u003Cp>Is there anything else you often come across in the digital health or AI in medicine realm and don’t really understand? Let us know, we are always happy to help! \u003C\u002Fp>\n",{"rendered":1648,"protected":16},"\u003Cp>Here is our survival guide in the bewildering world of digital health terminology. We’re decoding the lingo, from radiomics and theranostics to LLM and GenAI – ensuring you’re not just nodding along when discussing these topics. \u003C\u002Fp>\n",55371,{"_acf_changed":16,"footnotes":74},[78,5],[1653,950,1654],1038,7847,[92],[],[384,1658,1659,1446,381,96,97,754,383],1837,2303,[1661,63,103,104,105,106,107,108,109,1662,963,1663,121],"post-55367","tag-buzzword","tag-generative-ai-in-medicine",{"id":1649,"alt_text":74,"caption":74,"description":74,"media_type":124,"media_details":1665,"post":1371,"source_url":1692},{"width":761,"height":762,"file":1666,"filesize":1667,"sizes":1668,"image_meta":1690},"2024\u002F04\u002Ftmf_article_407.png",1575716,{"medium":1669,"large":1673,"thumbnail":1677,"medium_large":1681,"1536x1536":1682,"2048x2048":1686},{"file":1670,"width":418,"height":419,"mime-type":135,"filesize":1671,"source_url":1672},"tmf_article_407-370x208.png",41755,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407-370x208.png",{"file":1674,"width":423,"height":424,"mime-type":135,"filesize":1675,"source_url":1676},"tmf_article_407-768x432.png",114428,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407-768x432.png",{"file":1678,"width":428,"height":428,"mime-type":135,"filesize":1679,"source_url":1680},"tmf_article_407-150x150.png",19540,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407-150x150.png",{"file":1674,"width":423,"height":424,"mime-type":135,"filesize":1675,"source_url":1676},{"file":1683,"width":433,"height":434,"mime-type":135,"filesize":1684,"source_url":1685},"tmf_article_407-1536x864.png",297315,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407-1536x864.png",{"file":1687,"width":669,"height":670,"mime-type":135,"filesize":1688,"source_url":1689},"tmf_article_407-2048x1152.png",435933,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407-2048x1152.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":1691},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F04\u002Ftmf_article_407.png",{"cta_type":74,"cta_color":74,"related_books":16,"related_posts_footer":16,"related_posts":16,"subtitle":74,"key_takeaways":1694},[1695,1697],{"title":1696},"\u003Cp>Navigating AI in medicine and digital health can feel like ordering a coffee at that new hipster café downtown.\u003C\u002Fp>\n",{"title":1698},"\u003Cp>Here is our survival guide in the bewildering world of digital health terminology. We’re decoding the lingo, from radiomics and theranostics to LLM and GenAI – ensuring you’re not just nodding along when discussing these topics.\u003C\u002Fp>\n",{"yoast_wpseo_title":1700,"yoast_wpseo_metadesc":1701,"yoast_wpseo_canonical":1642},"A Buzzword Guide For Medical AI And Digital Health","Here is our survival guide in the bewildering world of digital health terminology, decoding the lingo, from radiomics and theranostics to LLM and GenAI. ",{"self":1703,"collection":1708,"about":1710,"author":1712,"replies":1714,"version-history":1717,"predecessor-version":1721,"wp:featuredmedia":1725,"wp:attachment":1728,"wp:term":1731,"curies":1742},[1704],{"href":1705,"targetHints":1706},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55367",{"allow":1707},[37],[1709],{"href":189},[1711],{"href":192},[1713],{"embeddable":51,"href":195},[1715],{"embeddable":51,"href":1716},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=55367",[1718],{"count":1719,"href":1720},17,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55367\u002Frevisions",[1722],{"id":1723,"href":1724},60541,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55367\u002Frevisions\u002F60541",[1726],{"embeddable":51,"href":1727},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F55371",[1729],{"href":1730},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=55367",[1732,1734,1736,1738,1740],{"taxonomy":11,"embeddable":51,"href":1733},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=55367",{"taxonomy":217,"embeddable":51,"href":1735},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=55367",{"taxonomy":220,"embeddable":51,"href":1737},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=55367",{"taxonomy":223,"embeddable":51,"href":1739},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=55367",{"taxonomy":226,"embeddable":51,"href":1741},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=55367",[1743],{"name":49,"href":50,"templated":51},{"id":1745,"date":1746,"date_gmt":1747,"guid":1748,"modified":1750,"modified_gmt":1751,"slug":1752,"status":62,"type":63,"link":1753,"title":1754,"content":1756,"excerpt":1758,"author":71,"featured_media":1760,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1761,"categories":1762,"tags":1763,"project_category":1766,"contact_email_category":1767,"yst_prominent_words":1768,"class_list":1774,"better_featured_image":1778,"acf":1799,"yoast_meta":1812,"_links":1815},51165,"2026-03-25T10:09:43","2026-03-25T09:09:43",{"rendered":1749},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=51165&_wpnonce=66b92b2f0d&status=auto-draft&type=post","2026-03-27T06:17:13","2026-03-27T05:17:13","the-current-state-of-fda-approved-ai-based-medical-devices","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-current-state-of-fda-approved-ai-based-medical-devices",{"rendered":1755},"The Current State Of Over 1450 FDA-Approved, AI-Based Medical Devices",{"rendered":1757,"protected":16},"\n\u003Cp>The rise of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftop-ai-algorithms-healthcare\" target=\"_blank\">has reshaped the industry\u003C\u002Fa>. And due to the recent march of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fchatgpt-in-healthcare-what-the-science-says\" target=\"_blank\">ChatGPT\u003C\u002Fa>, and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\" target=\"_blank\">similar tools\u003C\u002Fa>, various AI algorithms \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhere-is-how-you-get-friendly-with-a-i-before-it-gets-to-the-office\" target=\"_blank\">have entered the lives\u003C\u002Fa> of the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-can-you-use-ai-in-your-healthcare-right-now\u002F\" target=\"_blank\">general population\u003C\u002Fa> as well. These technologies \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-chatgpt-revolution-heres-our-new-book-on-generative-ai-in-healthcare\" target=\"_blank\">will undoubtedly change\u003C\u002Fa> the way \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-it-is-important-to-understand-multimodal-large-language-models-in-healthcare\u002F\" target=\"_blank\">medicine is practiced\u003C\u002Fa>. Given that healthcare is an industry where decisions can literally be a matter of life and death, the importance of effective regulation can’t be overstated. Now this is one hell of a challenge even for the most seasoned professionals.\u003C\u002Fp>\n\n\n\n\u003Cp>AI and ML present novel regulatory challenges. Unlike traditional medical devices, these technologies are \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Flocked-and-adaptive-algorithms-in-healthcare-differences-importance-and-regulatory-hurdles\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">capable of evolving and learning over time\u003C\u002Fa>. This means that they could perform differently in the real world than they did during their pre-market testing. While this could mean improved patient outcomes, it also could introduce new risks that need to be managed. Which is no easy task with a constantly changing algorithm. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1-768x432.png\" alt=\"\" class=\"wp-image-51171\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1.png 1600w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Historically, the FDA has been a global pioneer in regulating novel technologies in healthcare. From pharmaceuticals to medical devices, the FDA was traditionally setting standards, no wonder, all eyes seem to be on the American regulatory body these days. \u003C\u002Fp>\n\n\n\n\u003Cp>Traditionally, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fda.gov\u002Fmedical-devices\u002Fsoftware-medical-device-samd\u002Fartificial-intelligence-and-machine-learning-aiml-enabled-medical-devices\" target=\"_blank\">FDA updates its AI-enabled database\u003C\u002Fa> once a year, always in the fall months, so it was time to take a look at what we can learn from the latest available statistics. \u003C\u002Fp>\n\n\n\n\u003Cp>Now the FDA database has a total of 1451 devices (up from 1250 last year). As of March, 2026, no device has been authorized that uses generative AI or is powered by large language models.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>From zero to hero\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>A few years ago, the regulatory landscape for AI and ML technologies was almost non-existent. Medical device approvals didn’t explicitly indicate if a technology was AI-based. This made it difficult for healthcare professionals, patients, and other stakeholders to understand the extent to which AI was being integrated into healthcare solutions. Inventors and developers are also seriously hindered as they see no clear path to market approval of new technologies. It’s crucial to distinguish these AI-based technologies because they carry unique considerations and implications for users and patients.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1436\" height=\"1080\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-2.png\" alt=\"AI-based medical devices\" class=\"wp-image-51173\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-2.png 1436w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-2-768x578.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-2-1536x1155.png 1536w\" sizes=\"auto, (max-width: 1436px) 100vw, 1436px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">For the full-size version, right-click on the image and open in a new tab\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The FDA has been approving AI-based devices for years but didn’t initially distinguish them as a unique category. A few years back, we at The Medical Futurist Institute took it upon ourselves to sift through all these approvals and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-020-00324-0\" target=\"_blank\">identify the ones that were AI-based\u003C\u002Fa>. From our work, we created an open-access database, which we shared with the FDA so they could build on our groundwork. To our gratification, a year later, the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fda.gov\u002Fmedical-devices\u002Fsoftware-medical-device-samd\u002Fartificial-intelligence-and-machine-learning-aiml-enabled-medical-devices\" target=\"_blank\">FDA published its own database\u003C\u002Fa> and cited us as a source.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>The exponential growth we witness now\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"845\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-768x845.jpg\" alt=\"\" class=\"wp-image-60507\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-768x845.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-1396x1536.jpg 1396w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>To date, the most recent database shows a total of 1250 approvals. Look how sharply this number has been rising:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>1995: 2\u003C\u002Fli>\n\n\n\n\u003Cli>1997: 1\u003C\u002Fli>\n\n\n\n\u003Cli>1998: 2\u003C\u002Fli>\n\n\n\n\u003Cli>2001: 2\u003C\u002Fli>\n\n\n\n\u003Cli>2002: 1\u003C\u002Fli>\n\n\n\n\u003Cli>2004: 1\u003C\u002Fli>\n\n\n\n\u003Cli>2005: 1\u003C\u002Fli>\n\n\n\n\u003Cli>2006: 1\u003C\u002Fli>\n\n\n\n\u003Cli>2008: 5\u003C\u002Fli>\n\n\n\n\u003Cli>2010: 3\u003C\u002Fli>\n\n\n\n\u003Cli>2011: 3\u003C\u002Fli>\n\n\n\n\u003Cli>2012: 5\u003C\u002Fli>\n\n\n\n\u003Cli>2013: 4\u003C\u002Fli>\n\n\n\n\u003Cli>2014: 6\u003C\u002Fli>\n\n\n\n\u003Cli>2015: 6\u003C\u002Fli>\n\n\n\n\u003Cli>2016: 18\u003C\u002Fli>\n\n\n\n\u003Cli>2017: 27\u003C\u002Fli>\n\n\n\n\u003Cli>2018: 65\u003C\u002Fli>\n\n\n\n\u003Cli>2019: 80\u003C\u002Fli>\n\n\n\n\u003Cli>2020: 114\u003C\u002Fli>\n\n\n\n\u003Cli>2021: 130\u003C\u002Fli>\n\n\n\n\u003Cli>2022: 163\u003C\u002Fli>\n\n\n\n\u003Cli>2023: 226\u003C\u002Fli>\n\n\n\n\u003Cli>2024: 236\u003C\u002Fli>\n\n\n\n\u003Cli>2025: 350  \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Which specialties are most affected?\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>According to our latest data analysis, \u003Ca href=\"https:\u002F\u002Faicentral.acrdsi.org\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">radiology stands out\u003C\u002Fa> as the most AI-invested medical specialty, boasting a whopping 1104 approved devices. A distant second is \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffuture-of-cardiology\" target=\"_blank\" rel=\"noreferrer noopener\">cardiology\u003C\u002Fa> or cardiovascular (as a category), with 141 devices.\u003C\u002Fp>\n\n\n\n\u003Cp>Beyond that, other specialties (neurology, hematology, gastroenterology-urology and ophthalmology among others) see a handful of devices. What propelled imaging to such heights? Well, deep learning found a \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-radiology-and-ai\" target=\"_blank\">fertile ground in radiology\u003C\u002Fa>, which is largely data-driven. \u003C\u002Fp>\n\n\n\n\u003Cp>Here is the full list:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Radiology 1104\u003C\u002Fli>\n\n\n\n\u003Cli>Cardiovascular 141\u003C\u002Fli>\n\n\n\n\u003Cli>Neurology 67\u003C\u002Fli>\n\n\n\n\u003Cli>Anesthesiology 27\u003C\u002Fli>\n\n\n\n\u003Cli>Gastroenterology-Urology 26\u003C\u002Fli>\n\n\n\n\u003Cli>Hematology 21\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>The FDA submission types\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>The FDA recognises three distinct submission types: the 510(k), pre-market approval, and the De Novo pathway. By a long shot, \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>the 510(k) is the most popular with 1396 (+201 since last year) approvals so far,\u003C\u002Fli>\n\n\n\n\u003Cli>leaving De Novo 37 (+1)\u003C\u002Fli>\n\n\n\n\u003Cli>and pre-market 18 (+2) far behind. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>No wonder 510(k) is so popular, simply put, it’s the easiest route, as it is the pathway used for devices that are substantially equivalent to another legally marketed device. No new clinical trials are needed, although companies need to prove that their device is as safe and as effective as the already approved one. \u003C\u002Fp>\n\n\n\n\u003Cp>Meanwhile, pre-market approval is the most stringent type of device marketing application process. It is for high-risk devices, and it requires the manufacturer to provide clinical evidence demonstrating the safety and effectiveness of the device. This often involves clinical trials, which in turn makes it expensive. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-768x432.png\" alt=\"\" class=\"wp-image-51169\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage.png 1600w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The De Novo pathway is a regulatory pathway for low- to moderate-risk devices that are novel and for which there are no legally marketed predicate devices. It is suitable for Class I or II (lower-risk classifications) medical devices.\u003C\u002Fp>\n\n\n\n\u003Cp>We will continue to monitor this field, given that the FDA’s approach can set a valuable precedent for regulatory bodies in other countries. So, buckle up and stay tuned – there will be a lot to learn in the coming few years.\u003C\u002Fp>\n",{"rendered":1759,"protected":16},"\u003Cp>Given that healthcare is an industry where decisions can literally be a matter of life and death, the importance of effective regulation can’t be overstated. Now this is one hell of a challenge even for the most seasoned professionals.\u003C\u002Fp>\n",30807,{"_acf_changed":16,"footnotes":74},[5],[84,85,86,1764,365,87,949,950,1765],236,7827,[92],[],[384,257,1769,1770,1771,1772,1773,256,754],2017,3841,4295,4505,5067,[1775,63,103,104,105,106,107,109,114,115,116,1776,402,117,962,963,1777,121],"post-51165","tag-fda-2","tag-ai-based-medical-devices",{"id":1760,"alt_text":1779,"caption":74,"description":74,"media_type":124,"media_details":1780,"post":1797,"source_url":1798},"algorithm, deep learning, tmf",{"width":126,"height":127,"file":1781,"sizes":1782,"image_meta":1796},"2020\u002F10\u002F214_tmf-01-1.png",{"medium":1783,"large":1786,"thumbnail":1789,"medium_large":1792,"1536x1536":1793},{"file":1784,"width":133,"height":134,"mime-type":135,"source_url":1785},"214_tmf-01-1-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-370x208.png",{"file":1787,"width":140,"height":141,"mime-type":135,"source_url":1788},"214_tmf-01-1-768x432.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-768x432.png",{"file":1790,"width":146,"height":146,"mime-type":135,"source_url":1791},"214_tmf-01-1-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-150x150.png",{"file":1787,"width":140,"height":141,"mime-type":135,"source_url":1788},{"file":1794,"width":152,"height":153,"mime-type":135,"source_url":1795},"214_tmf-01-1-1536x864.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-1536x864.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},14484,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1.png",{"cta_type":166,"cta_color":74,"related_books":1800,"related_posts_footer":1801,"related_posts":16,"subtitle":74,"key_takeaways":1805},[998,1118,997],[1802,1803,1804],27125,53971,53645,[1806,1808,1810],{"title":1807},"\u003Cp>The FDA, a global leader in healthcare regulation, is adapting its framework to include AI-based medical devices, with 1400 approvals and clearances to date, indicating an acknowledgment of AI’s expanding role in healthcare.\u003C\u002Fp>\n",{"title":1809},"\u003Cp>The rise of AI in healthcare is revolutionizing medical practice, presenting unique regulatory challenges given AI’s evolving nature, which necessitates effective oversight to manage potential risks.\u003C\u002Fp>\n",{"title":1811},"\u003Cp>Radiology leads in AI device approvals reflecting deep learning’s applicability in image-based diagnostics, while the 510(k) submission pathway is predominant due to its streamlined process for devices similar to existing ones.\u003C\u002Fp>\n",{"yoast_wpseo_title":1813,"yoast_wpseo_metadesc":1814,"yoast_wpseo_canonical":1753},"The Current State Of FDA-Approved AI-Enabled Medical Devices","Decisions in healthcare can be a matter of life and death, the importance of effective regulation can't be overstated. One hell of a challenge with AI.",{"self":1816,"collection":1821,"about":1823,"author":1825,"replies":1827,"version-history":1830,"predecessor-version":1834,"wp:featuredmedia":1838,"wp:attachment":1841,"wp:term":1844,"curies":1855},[1817],{"href":1818,"targetHints":1819},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51165",{"allow":1820},[37],[1822],{"href":189},[1824],{"href":192},[1826],{"embeddable":51,"href":195},[1828],{"embeddable":51,"href":1829},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=51165",[1831],{"count":1832,"href":1833},31,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51165\u002Frevisions",[1835],{"id":1836,"href":1837},60529,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F51165\u002Frevisions\u002F60529",[1839],{"embeddable":51,"href":1840},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F30807",[1842],{"href":1843},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=51165",[1845,1847,1849,1851,1853],{"taxonomy":11,"embeddable":51,"href":1846},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=51165",{"taxonomy":217,"embeddable":51,"href":1848},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=51165",{"taxonomy":220,"embeddable":51,"href":1850},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=51165",{"taxonomy":223,"embeddable":51,"href":1852},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=51165",{"taxonomy":226,"embeddable":51,"href":1854},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=51165",[1856],{"name":49,"href":50,"templated":51},{"id":1858,"date":1859,"date_gmt":1860,"guid":1861,"modified":1863,"modified_gmt":1864,"slug":1865,"status":62,"type":63,"link":1866,"title":1867,"content":1869,"excerpt":1871,"author":246,"featured_media":1873,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1874,"categories":1875,"tags":1876,"project_category":1877,"contact_email_category":1878,"yst_prominent_words":1879,"class_list":1884,"better_featured_image":1887,"acf":1908,"yoast_meta":1916,"_links":1918},57969,"2026-03-09T10:26:02","2026-03-09T09:26:02",{"rendered":1862},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=57969&_wpnonce=4fe90e0a49&status=auto-draft&type=post","2026-03-09T10:26:03","2026-03-09T09:26:03","surgical-robots-current-uses-and-future-expectations","https:\u002F\u002Fmedicalfuturist.com\u002Fsurgical-robots-current-uses-and-future-expectations",{"rendered":1868},"Surgical Robots: Current Uses and Future Expectations",{"rendered":1870,"protected":16},"\n\u003Cp>A staple of science fiction, robots have stirred human creativity since ancient times; and well before the term itself was coined \u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fkarel-capek-robots\" target=\"_blank\" rel=\"noreferrer noopener\">by the Čapek brothers\u003C\u002Fa> in 1921. Homer’s Iliad features \u003Ca href=\"https:\u002F\u002Fnovoscriptorium.com\u002F2019\u002F04\u002F23\u002Frobotics-and-artificial-integillence-in-the-homeric-epics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">automatons\u003C\u002Fa> while more recent works like \u003Cem>The Terminator\u003C\u002Fem> merge robots and artificial intelligence (AI) to depict doomsday scenarios. Far from the latter apocalyptic scenario, robots have made it past the sci-fi realm and into \u003Ca href=\"https:\u002F\u002Fwww.hp.com\u002Fus-en\u002Fshop\u002Ftech-takes\u002Feveryday-robotics\" target=\"_blank\" rel=\"noreferrer noopener\">our everyday lives\u003C\u002Fa>. We have grown used to the sight of robot vacuum cleaners in our homes as we have shelf-stacking robots in warehouses.\u003C\u002Fp>\n\n\n\n\u003Cp>The resilience of robots and their imperviousness to human traits such as fatigue have also made them apt \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedical-robots\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">assistants in healthcare\u003C\u002Fa>. They have made strides in the field of surgery for their precision and speed. This article will cover the surgical robot landscape and contemplate what we can expect from these mechanical assistants in the future.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What are surgical robots?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called \u003Ca href=\"https:\u002F\u002Fwww.mayoclinic.org\u002Ftests-procedures\u002Frobotic-surgery\u002Fabout\u002Fpac-20394974\" target=\"_blank\" rel=\"noreferrer noopener\">robotic surgeries\u003C\u002Fa> or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre. \u003C\u002Fp>\n\n\n\n\u003Cp>While robots in the OT might sound futuristic, they have assisted surgeons for decades already. As far back as 1985, surgical robots would assist in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1878788611000324\" target=\"_blank\">performing brain biopsies\u003C\u002Fa>. Over the years, the surgical robots market is a booming one and is expected to reach \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.saranextgen.com\u002Fhomeworkhelp\u002Findex.php?id=3071\" target=\"_blank\">$14.8 billion by 2027\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"384\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F03\u002Frobotic-surgery-isometric-icons-set-768x384.jpg\" alt=\"\" class=\"wp-image-15115\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F03\u002Frobotic-surgery-isometric-icons-set-768x384.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F03\u002Frobotic-surgery-isometric-icons-set-512x256.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F03\u002Frobotic-surgery-isometric-icons-set-458x229.jpg 458w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F03\u002Frobotic-surgery-isometric-icons-set.jpg 870w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Robotic surgery isometric icons set with  surgeons patients and medical robots with widescreen touch screen and touch control isolated vector illustration\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>A popular surgical robot is the \u003Ca href=\"https:\u002F\u002Fwww.intuitive.com\u002Fen-us\u002Fproducts-and-services\u002Fda-vinci\u002F5\" target=\"_blank\" rel=\"noreferrer noopener\">da Vinci surgical system\u003C\u002Fa> from Intuitive Surgical. First launched in 2000, the system involves an array of agile and dexterous mechanical arms that can bend and rotate to a far greater extent than the human hand. Human surgeons are always guiding these arms at a surgeon console to carry out more precise operations. \u003C\u002Fp>\n\n\n\n\u003Cp>Since the da Vinci system was first introduced, Intuitive Surgical has developed newer models and now has fifth-generation da Vinci systems. Over the two decades, more than 8,600 da Vinci systems have been adopted across 71 countries. This evolution shows a growing adoption of the surgical robots as well as a need for such assistants in conducting surgical procedures.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The need for and current use of surgical robotic assistants \u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>One might question the need for surgical robots in procedures that require human dexterity and agility. In fact, those skills are enhanced by the mechanical assistants. Surgical robots have highly flexible arms that enable surgeons to perform \u003Ca href=\"https:\u002F\u002Fwww.mayoclinic.org\u002Ftests-procedures\u002Frobotic-surgery\u002Fabout\u002Fpac-20394974\" target=\"_blank\" rel=\"noreferrer noopener\">complex and delicate procedures\u003C\u002Fa> that would otherwise be challenging or even impossible. For example, the \u003Ca href=\"https:\u002F\u002Frobotics-surgical.com\u002Fflex-robotics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Flex robotic system\u003C\u002Fa> provides ENT surgeons with \u003Ca href=\"https:\u002F\u002Fwww.computerworld.com\u002Farticle\u002F1658250\u002Fa-robot-will-likely-assist-in-your-future-surgery.html\" target=\"_blank\" rel=\"noreferrer noopener\">sub-millimeter accuracy\u003C\u002Fa> across non-linear winding paths through a single-site access into the body.\u003C\u002Fp>\n\n\n\n\u003Cp>Indeed, robotic surgeries are key in performing \u003Ca href=\"https:\u002F\u002Fwww.mayoclinic.org\u002Ftests-procedures\u002Frobotic-surgery\u002Fabout\u002Fpac-20394974\" target=\"_blank\" rel=\"noreferrer noopener\">minimally invasive surgery\u003C\u002Fa>, where the surgery is done via small skin incisions. Through such an approach, patients \u003Ca href=\"https:\u002F\u002Fwww.computerworld.com\u002Farticle\u002F1563559\u002Freport-for-heart-surgery-robot-beats-a-surgeon.html\" target=\"_blank\" rel=\"noreferrer noopener\">have less complications\u003C\u002Fa>, heal faster and have shorter hospital stays. The da Vinci system allows for heart bypass surgery through a couple of \u003Ca href=\"https:\u002F\u002Fwww.computerworld.com\u002Farticle\u002F1658250\u002Fa-robot-will-likely-assist-in-your-future-surgery.html\" target=\"_blank\" rel=\"noreferrer noopener\">one centimetre chest incisions\u003C\u002Fa> instead of one-foot long opening required for traditional means. \u003Ca href=\"https:\u002F\u002Fwww.intuitive.com\u002Fen-us\u002Fpatients\u002Fda-vinci-robotic-surgery\" target=\"_blank\" rel=\"noreferrer noopener\">Over 14 million\u003C\u002Fa> surgical procedures have made use of the system worldwide.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_264-01-768x432.png\" alt=\"future jobs in healthcare\" class=\"wp-image-34321\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_264-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_264-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_264-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_264-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Beyond incisions, surgical robots also assist in other procedures. The \u003Ca href=\"https:\u002F\u002Fcmrsurgical.com\u002Fversius\" target=\"_blank\" rel=\"noreferrer noopener\">Versius Surgical Robotic System\u003C\u002Fa> can perform \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC9267445\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">laparoscopies\u003C\u002Fa> ranging from thoracic to urological procedures. The \u003Ca href=\"https:\u002F\u002Fwww.jnjmedtech.com\u002Fen-US\u002Fproduct-family\u002Fmonarch\" target=\"_blank\" rel=\"noreferrer noopener\">MONARCH platform\u003C\u002Fa> has been used to complete \u003Ca href=\"https:\u002F\u002Fwww.jnjmedtech.com\u002Fen-US\u002Fproduct\u002Fmonarch-bronchoscopy\" target=\"_blank\" rel=\"noreferrer noopener\">over 20,000 lung biopsies\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>Surgical robots also assist in radiosurgeries. These involve very focused radiation beams for the treatment of cancer tissues. Accuray’s \u003Ca href=\"https:\u002F\u002Fwww.accuray.com\u002Fcyberknife\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">CyberKnife\u003C\u002Fa> provides robotic radiation treatment anywhere in the body with sub-millimeter accuracy. The company notes that over 350 systems have been installed globally to treat \u003Ca href=\"https:\u002F\u002Fwww.computerworld.com\u002Farticle\u002F1658250\u002Fa-robot-will-likely-assist-in-your-future-surgery.html\" target=\"_blank\" rel=\"noreferrer noopener\">more than 40,000 patients\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>AI and the automation of surgical robots\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Using the assistance of robots to perform surgeries already sounds futuristic but there is a future beyond their current use. In particular, \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC10445506\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">researchers foresee\u003C\u002Fa> the combination of AI technologies with surgical robots. Deep learning models could aid surgical robots in learning from experience, akin to a trainee surgeon. They could create and suture surgical incisions; a task that AI-controlled robotic systems have undertaken with precision in \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC10839429\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">previous studies\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>As AI-powered surgical robots progress through \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-levels-of-automation-in-medicine\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">levels of automation\u003C\u002Fa>, they will become more and more independent. Below we provide a brief description of each of the 5 levels of automation and how they relate to surgical robots. For a more in-depth explanation of these levels, we have dedicated \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-levels-of-automation-in-medicine\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">a separate article\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Automation level 1: human only\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>The initial level involves no AI software. This is the level at which most, if not all, surgical robots are at in practice. They are under human control and essentially act as extensions of the surgeons’ arms.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Automation level 2: shadow mode\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>A surgical robot with level 2 automation will be equipped with AI software in “shadow mode”. It will still be under the surgeon’s control but it will learn from the latter so that it can progress through the automation spectrum.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Automation level 3: AI assistance\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>With enough training, a level 3 surgical robot can provide autonomous assistance to surgeons. It can suggest adequate procedures and techniques which can then be signed off by human surgeons.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Automation level 4: partial automation\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>As the AI software underpinning surgical robots gain more experience and become more confident, a level 4 surgical robot could independently assist surgeons, whether it is through devising surgical techniques or conducting procedures. If it is not confident enough, it will turn to human surgeons for assistance.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">\u003Cstrong>Automation level 5: full automation\u003C\u002Fstrong>\u003C\u002Fh3>\n\n\n\n\u003Cp>At the 5th automation level, a surgical robot would be able to perform surgeries on its own. It will not require human supervision or input for its own decisions. \u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"1292\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation-768x1292.png\" alt=\"\" class=\"wp-image-47253\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation-768x1292.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation.png 642w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Steps to combine AI and robots for surgical ends are \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC10839429\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">still in their infancy\u003C\u002Fa>; but over time we can expect such a merger to materialise. Before AI-powered surgical robots make their way to the OT, their safety will need to be ensured and they will need to be supervised by expert surgeons. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The future of robots in the realm of surgeries \u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Through technological progress, we can expect more from surgical robots in the future. For example, at higher levels of automation, surgical robots would be able to make \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC10839429\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">telesurgery\u003C\u002Fa> more accessible. This would enable surgical procedures to be conducted \u003Ca href=\"https:\u002F\u002Fblog.engineering.vanderbilt.edu\u002Fthe-future-of-robotic-surgery-3-trends-to-look-for\" target=\"_blank\" rel=\"noreferrer noopener\">in remote or under-resourced areas\u003C\u002Fa> in order to improve health outcomes.\u003C\u002Fp>\n\n\n\n\u003Cp>We can also expect surgical robots to \u003Ca href=\"https:\u002F\u002Fblog.engineering.vanderbilt.edu\u002Fthe-future-of-robotic-surgery-3-trends-to-look-for\" target=\"_blank\" rel=\"noreferrer noopener\">become smaller\u003C\u002Fa>. This would make them even less invasive than they currently are. \u003Ca href=\"https:\u002F\u002Fblog.engineering.vanderbilt.edu\u002Fthe-future-of-robotic-surgery-3-trends-to-look-for\" target=\"_blank\" rel=\"noreferrer noopener\">Micro-robots\u003C\u002Fa>, for example, could even perform targeted surgeries through GI insertion with no external incisions.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Ftmf_article_428-768x432.png\" alt=\"\" class=\"wp-image-57617\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Ftmf_article_428-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Ftmf_article_428-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Ftmf_article_428-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F08\u002Ftmf_article_428-2048x1152.png 2048w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Above all, it’s a surgeon-AI-robot collaboration that we should expect rather than fully mechanised procedures. You can think about it as a souped-up version of the current existing assistance of robots that already help perform tens of thousands of surgeries every year. With more automation in the mix, the healthcare landscape stands to benefit from the potential of more precise and more accessible surgeries. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",{"rendered":1872,"protected":16},"\u003Cp>As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre. \u003C\u002Fp>\n",34403,{"_acf_changed":16,"footnotes":74},[78,5,438],[],[],[],[1880,1881,1882,1883],2373,3229,3347,2145,[1885,63,103,104,105,106,107,108,109,1886],"post-57969","category-robotics",{"id":1873,"alt_text":74,"caption":74,"description":1888,"media_type":124,"media_details":1889,"post":1906,"source_url":1907},"The future of surgery robot robotic robotic-assisted TMF ",{"width":126,"height":127,"file":1890,"sizes":1891,"image_meta":1905},"2021\u002F05\u002Ftmf_article_267-01.png",{"medium":1892,"large":1895,"thumbnail":1898,"medium_large":1901,"1536x1536":1902},{"file":1893,"width":133,"height":134,"mime-type":135,"source_url":1894},"tmf_article_267-01-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-370x208.png",{"file":1896,"width":140,"height":141,"mime-type":135,"source_url":1897},"tmf_article_267-01-768x432.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png",{"file":1899,"width":146,"height":146,"mime-type":135,"source_url":1900},"tmf_article_267-01-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-150x150.png",{"file":1896,"width":140,"height":141,"mime-type":135,"source_url":1897},{"file":1903,"width":152,"height":153,"mime-type":135,"source_url":1904},"tmf_article_267-01-1536x864.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-1536x864.png",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163},34359,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01.png",{"cta_type":74,"cta_color":74,"subtitle":74,"key_takeaways":1909,"related_books":16,"related_posts_footer":16,"related_posts":16},[1910,1912,1914],{"title":1911},"\u003Cp>Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.\u003C\u002Fp>\n",{"title":1913},"\u003Cp>Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.\u003C\u002Fp>\n",{"title":1915},"\u003Cp>The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.\u003C\u002Fp>\n",{"yoast_wpseo_title":1917,"yoast_wpseo_metadesc":74,"yoast_wpseo_canonical":1866},"Surgical Robots: Current Uses and Future Expectations - The Medical Futurist",{"self":1919,"collection":1924,"about":1926,"author":1928,"replies":1930,"version-history":1933,"predecessor-version":1936,"wp:featuredmedia":1940,"wp:attachment":1943,"wp:term":1946,"curies":1957},[1920],{"href":1921,"targetHints":1922},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57969",{"allow":1923},[37],[1925],{"href":189},[1927],{"href":192},[1929],{"embeddable":51,"href":300},[1931],{"embeddable":51,"href":1932},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=57969",[1934],{"count":816,"href":1935},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57969\u002Frevisions",[1937],{"id":1938,"href":1939},57981,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F57969\u002Frevisions\u002F57981",[1941],{"embeddable":51,"href":1942},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F34403",[1944],{"href":1945},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=57969",[1947,1949,1951,1953,1955],{"taxonomy":11,"embeddable":51,"href":1948},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=57969",{"taxonomy":217,"embeddable":51,"href":1950},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=57969",{"taxonomy":220,"embeddable":51,"href":1952},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=57969",{"taxonomy":223,"embeddable":51,"href":1954},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=57969",{"taxonomy":226,"embeddable":51,"href":1956},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=57969",[1958],{"name":49,"href":50,"templated":51},[1960],{"id":21,"date":1961,"date_gmt":1962,"guid":1963,"modified":1965,"modified_gmt":1966,"slug":1967,"status":62,"type":63,"link":1968,"title":1969,"content":1971,"excerpt":1973,"author":71,"featured_media":1975,"comment_status":73,"ping_status":73,"sticky":51,"template":74,"format":75,"meta":1976,"categories":1977,"tags":1978,"project_category":1988,"contact_email_category":1989,"yst_prominent_words":1990,"class_list":1996,"better_featured_image":2007,"acf":2036,"yoast_meta":2044,"_links":2047},"2025-10-06T09:29:02","2025-10-06T07:29:02",{"rendered":1964},"http:\u002F\u002Fmedicalfuturist.com\u002F?p=15909","2025-10-06T09:29:03","2025-10-06T07:29:03","the-future-of-radiology-and-ai","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-radiology-and-ai",{"rendered":1970},"The Future of Radiology And Artificial Intelligence",{"rendered":1972,"protected":16},"\n\n\n\u003Cp>What if an algorithm could tell you whether you have cancer based on your CT scan or mammography exam? While I am confident that radiologists’ creative work will be necessary in the future to solve complex issues and supervise diagnostic processes, A.I. will definitely become part of their daily routine in diagnosing simpler cases and taking over repetitive tasks. So rather than getting threatened by it, we should familiarise ourselves with how it could help change the course of radiology for the better.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Radiologists who use AI will replace those who don’t\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>There is a lot of hype and plenty of fear around artificial intelligence and its impact on the future of healthcare. There are many signs pointing toward the fact that \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fartificial-intelligence-will-redesign-healthcare\u002F\" target=\"_blank\">A.I. will completely move the world of medicine\u003C\u002Fa>. As deep learning algorithms and narrow A.I. started to buzz especially around the field of medical imaging, many radiologists went into panic mode. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"768\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002FAI-not-replace-physicians-768x768.jpg\" alt=\"\" class=\"wp-image-47245\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002FAI-not-replace-physicians-768x768.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002FAI-not-replace-physicians-150x150.jpg 150w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002FAI-not-replace-physicians.jpg 800w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Bradley Erickson, Director of the Radiology Informatics Lab at Mayo Clinic told me that some of the hype we hear from some of the machine learning and deep learning experts saying that A.I. would replace radiologists is looking at radiologists as if they were just looking at pictures. \u003Cem>That would be me saying while I look at programmers, all they do is typing, so we can replace a programmer with a speech recognition system\u003C\u002Fem>, he added. Langlotz compared the situation to that of the autopilot in aviation. The innovation did not replace real pilots, it only augmented their tasks. On very long flights, it is handy to turn on the autopilot, but they are useless when you need rapid judgment. So, the combination of humans and machines is the winning solution. And it will be the same in healthcare.\u003C\u002Fp>\n\n\n\n\u003Cp>Thus, I agree with Langlotz completely when he says that \u003Cem>artificial intelligence will not replace radiologists. Yet, those radiologists who use A.I. will replace the ones who don’t\u003C\u002Fem>. Let me show you why.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What do cat intestines, X-ray lamps and the history of medical imaging have in common?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The field of clinical radiology started obviously with the quite \u003Ca href=\"http:\u002F\u002Fstatic.springer.com\u002Fsgw\u002Fdocuments\u002F1426506\u002Fapplication\u002Fpdf\u002FVan+Gelderen_A+Brief+History+of+Radiology.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">coincidental discovery of the X-ray by Wilhelm Conrad Röntgen on 8 November 1895 in Würzburg, Germany\u003C\u002Fa>. Within two months, the X-ray mania ran over the world. Sensational headlines in newspapers propagated the “new light seeing through flesh to bones”, while one inventor even speculated that “soon every house will have a cathode-ray machine”. Any similarities about hyped technologies coming to mind?\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"870\" height=\"536\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fwilhelm-conrad-röntgen-and-x-ray.png\" alt=\"Future of Radiology\" class=\"wp-image-15911\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fwilhelm-conrad-röntgen-and-x-ray.png 870w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fwilhelm-conrad-röntgen-and-x-ray-768x473.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fwilhelm-conrad-röntgen-and-x-ray-512x315.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fwilhelm-conrad-röntgen-and-x-ray-406x250.png 406w\" sizes=\"auto, (max-width: 870px) 100vw, 870px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Thomas Edison became so excited about the new discovery that he even wanted to create a commercial “X-ray lamp” (unfortunately, his efforts failed) and tried to get an X-ray of the human brain in action (sadly, that was not a success either). His latter endeavour let story-driven reporters go nuts: they were allegedly waiting for the innovation outside his laboratory for weeks in vain. Some went as far as to fabricate images about the human brain. One of them turned out to be a pan of cat intestines radiographed in 1896 by H. A. Falk!\u003C\u002Fp>\n\n\n\n\u003Cp>While some early efforts turned out to be huge blows and impossible projects, X-rays got acclimatised in medicine. Something similar will happen with A.I. and healthcare soon. I hope with fewer cat intestines, though.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Radiology has been the playfield of technological development since the beginnings\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In the TV series, \u003Cem>The Knick\u003C\u002Fem> depicting the first decades of modern surgery and healthcare, an inventor gets in touch with the hospital manager in his office to present him with a new idea, the X-ray machine. It turns out that it takes an hour or so for the brand-new machine to take the picture! Currently, if you go to the hospital to get the annual check-up on your lungs done, the X-ray procedure will take a couple of minutes in a fortunate situation, and some more until you get the results.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"The Knick S01E06 X ray scene 2 1\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FU7XOYZsnTxM?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Plenty has changed since those experiments with the ‘X-ray lamp’, but one thing was constant: rapid technological development in radiology.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>A bigger range of tools and higher precision\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Approximately half a century after the discovery of the X-ray, ultrasound joined the methods of medical imaging. From the mid-sixties onwards, the advent of commercially available systems allowed wider dissemination. Rapid technological advances in electronics and piezoelectric materials provided further improvements from bistable to greyscale images and from still images to real-time moving images. And it is also amazing to see how we went from room-sized, clumsy ultrasound machines to portable ones circa within another half of a century! In 2016, Clarius Mobile Health introduced the world’s first handheld ultrasound scanner with a mobile application. The doctor can carry around the personal ultrasound device for quick exams and to guide procedures such as nerve blocks and targeted injections.\u003C\u002Fp>\n\n\n\n\u003Cp>Now, let’s look at body scanners. The first CT scanners were\u003Ca href=\"https:\u002F\u002Fradiopaedia.org\u002Farticles\u002Fct-scanner-evolution\"> introduced in 1971 with a single detector for brain study under the leadership of Godfrey Hounsfield\u003C\u002Fa>, an electrical engineer at EMI (Electric and Musical Industries, Ltd). The very first \u003Ca href=\"http:\u002F\u002Fwww.two-views.com\u002Fmri-imaging\u002Fhistory.html#sthash.RbPBZETW.dpbs\">MRI scanner was built by Raymond Damadian in the 1970s by hand\u003C\u002Fa>, assisted by his students at New York’s Downstate Medical Center. He achieved the first MRI scan of a healthy human body in 1977 and a human organism with cancer in 1978. The first functional MR imaging of the human brain is produced in the early 1990s. By the early 2000s, cardiac MRI, body MRI, fetal imaging, and functional MR imaging became routine exams in many imaging centers.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"870\" height=\"785\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fmedical-imaging-techniques.jpg\" alt=\"Future of Radiology\" class=\"wp-image-15912\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fmedical-imaging-techniques.jpg 870w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fmedical-imaging-techniques-768x693.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fmedical-imaging-techniques-512x462.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fmedical-imaging-techniques-277x250.jpg 277w\" sizes=\"auto, (max-width: 870px) 100vw, 870px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>\u003Cstrong>Along with precision comes automation \u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Thus, the history of radiology shows the expansion of means as well as the increase in precision so far. While the latter is still in focus, there is also a visible shift towards making radiologists’ lives easier by automation. As radiologists need to go through more and more images every day, it becomes inevitable that part of their job can be automated. When we can train algorithms to spot and detect many types of abnormalities based on radiology images, why wouldn’t we let it do the time-consuming job so we can let radiologists dedicate their precious focus to the hardest issues?\u003C\u002Fp>\n\n\n\n\u003Cp>When deep learning becomes possible and the algorithm could teach itself while radiologists rate its effectiveness, it’s going to get better just by working more. This is an opportunity we have to grab. This way radiology would be one of the most creative specialities in which problem-solving and a holistic approach would be the key.\u003C\u002Fp>\n\n\n\n\u003Cp>So, it certainly would not mean that A.I. would take over all the tasks of radiologists. As Erickson put it, if you look at the frequency of findings and diagnoses on medical images\u003Cem>, there are the common ones where AI\u003C\u002Fem> \u003Cem>could help, but there is a really long tail, uncommon but really important things that we cannot miss\u003C\u002Fem>. He believes that it is going to be difficult for deep learning algorithms to identify those. But where do we stand with technology at the moment?\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Could AI\u003C\u002Fstrong> \u003Cstrong>predict whether you would die soon?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Scientists at the University of Adelaide have been experimenting with an \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-017-01931-w#Fig4\" target=\"_blank\">AI system that is said to be able to tell if you are going to die\u003C\u002Fa>. By analysing CT scans from 48 patients, the deep learning algorithms could predict whether they’d die within five years with 69 percent accuracy.  It is “broadly similar” to scores from human diagnosticians, the paper says. It is an impressive achievement. The deep learning system was trained to analyse over 16,000 image features that could indicate signs of disease in those organs. Researchers say that their goal is for the algorithm to measure overall health rather than spot a single disease.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"660\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ffda-approvals-ai-algorithms-768x660.png\" alt=\"FDA-approved AI-based algorithms\" class=\"wp-image-33293\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ffda-approvals-ai-algorithms-768x660.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F03\u002Ffda-approvals-ai-algorithms.png 1257w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">To view the infographics in full size, right click and open in a new browser tab\u002Fwindow\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>This is just one of the numerous initiatives on developing artificial intelligence applications to support the field of radiology. You can take a look at this article published by The Medical Futurist Institute in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-020-00324-0\" target=\"_blank\">npj Digital Medicine journal\u003C\u002Fa>, or \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffda-approved-ai-based-algorithms\u002F\" target=\"_blank\">the online database\u003C\u002Fa> we keep updating ever since. It currently has 79 entries, of which 39 belong to the field of radiology. That is undisputedly the medical field with the highest number of AI initiatives. \u003C\u002Fp>\n\n\n\n\u003Cp>However, the ongoing research does not mean that we are already at the stage where average patients will have to face their exact life expectancy based on their medical images when they go to the hospital.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What are the challenges in introducing AI\u003C\u002Fstrong> \u003Cstrong>to the radiology department?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In order to have some estimation of when machine learning might be introduced on a wider scale, we have to look at how machine learning takes place in radiology. The process usually goes like this: the algorithm should be fed by thousands, if not millions of images and learn to spot differences regarding tissues. Just as in the case of computers recognising images of dogs and cats. If the algorithm makes a mistake, the researcher notices it and adjusts the code. Thus, it is a rather lengthy process that needs tons of available data. Erickson believes that the result will look like the following: we’ll do the high volume exam, and the algorithm will probably create a structured, minable, preliminary report. \u003Cem>So it will do the quantification that most humans hate to do and it will do that very well\u003C\u002Fem>, he noted.\u003C\u002Fp>\n\n\n\n\u003Cp>Anna Fernandez, Health Informatics\u002FPrecision Medicine Lead at Booz Allen Hamilton told me though that \u003Cem>there are several challenges in building these discovery and analytic platforms – from acquiring access and ingesting the data, sufficiently annotating the data, storage strategy, governance\u002Fpolicy use throughout, and types of analysis enabled via the platform.\u003C\u002Fem> The biggest challenge is sufficiently annotating the data to allow different views of it (full right to owners, restricted subset to others) and enable discovery across the connected data sets in the platform.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"870\" height=\"580\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fai-and-radiology.jpg\" alt=\"Future of Radiology\" class=\"wp-image-15917\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fai-and-radiology.jpg 870w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fai-and-radiology-768x512.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fai-and-radiology-512x341.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Fai-and-radiology-375x250.jpg 375w\" sizes=\"auto, (max-width: 870px) 100vw, 870px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Moreover, hospitals also need to be convinced that A.I. algorithms work. Fernandez believes that it will be a step-wise process by for example taking advantage of hybrid internal and external “crowdsourcing” with sufficiently anonymised data.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>For example, a vendor can have established data science algorithms based on anonymised data from their hospital network, then the new hospital can employ the algorithm and further refine it to the anonymised “local” data sets (that may include additional patient variables) to customise it to their population.\u003C\u002Fem> As the hospitals see a “win,” they may be encouraged to release a more restricted anonymised data set to contribute back to the vendor solution. So it’s a little bit similar to how you try to go into the cold water on a hot summer day. First, you look at other people doing it, then you realise it’s safe, so you put your toes in the water before entirely going under.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>We get to have AI analyzing our CT scans\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>How can we depict in a concise and easy-to-grasp way how the human-A.I. collaboration will unfold in the field of medicine in the years and decades to come? Andrew Ng, founder of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.deeplearning.ai\u002F\" target=\"_blank\">deeplearning.ai\u003C\u002Fa> described five levels of automation. The Medical Futurist implemented this concept in medicine, and explained these levels with current examples and future scenarios \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-levels-of-automation-in-medicine\u002F\" target=\"_blank\">in this article\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>Below is such an infographic that helps in visualising the spectrum of automation in medicine, ranging from human-only (level1) to fully automated (level5).\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"1292\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation-768x1292.png\" alt=\"\" class=\"wp-image-47253\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation-768x1292.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ftmf-5-levels-of-automation.png 642w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Future radiology is expected to work with level 3 (AI assistance) and level 4 (Partial automation) algorithms. What do these mean? \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>At the third level\u003C\u002Fstrong>, the AI system supports physicians in clinical decision-making via suggestions. For example, after scanning a database of chest CT scans, the A.I. considers the chest CT results of a patient being investigated and highlights suspicious signs. These signs are then further investigated by the physician. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>On level four\u003C\u002Fstrong>, with partial automation, an AI system can come up with its own diagnosis; but if it’s not confident enough about it, the AI turns to physicians for help. Several companies are working on such solutions today. A \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fbeholdai.wordpress.com\u002F2022\u002F08\u002F10\u002Fsouthend_backlog\u002F\" target=\"_blank\">practical example\u003C\u002Fa> is Behold’s Class IIa CE marked platform that is used by UK’s NHS Trust to help clear the radiology backlogs in lung cancer screening. It can process adult frontal Chest X-Ray examinations and has two key outputs. It either flags the image as “suspected lung cancer” and prioritises the patient for a radiologist consultation, or it identifies the image as normal – although the image will also be audited by a radiologist.\u003C\u002Fp>\n\n\n\n\u003Cp>Palo Alto-based Nines \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedcitynews.com\u002F2020\u002F04\u002Fnines-gets-fda-clearance-for-ai-to-flag-two-life-threatening-conditions\u002F?rf=1\" target=\"_blank\">developed an AI-system\u003C\u002Fa> that can identify potential cases of intracranial haemorrhage and mass effect from CT scans. It then flags those cases for radiologists to review.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Radiology’s Future is AI\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>All in all, research trends and experts underline how AI will revolutionise radiology in the long term. Thus, rather than neglecting it or feeling threatened by it, the medical community should embrace its achievements.\u003C\u002Fp>\n\n\n\n\u003Ch4 class=\"wp-block-heading\">\u003Cstrong>Yes, it is possible that a big chunk of the tasks radiologists do today will be automated, covering all repetitive, data-based tasks. It will free up capacities for more meaningful assignments, and the AI-based technologies themselves will be designed and controlled by radiologists.   \u003C\u002Fstrong>\u003C\u002Fh4>\n\n\n\n\u003Cp>As Erickson put it, rather than pushing off machine intelligence as being a threat to their job, instead, radiologists should engage it, because it’s something that can really help patients. I’m sure it will dramatically change what radiologists\u003Cem> will do over the next ten years, but you should also keep in mind that eventually, radiology ten years ago was nothing like what it is today.\u003C\u002Fem> So it is just one of those things where we need to make sure that we keep at the forefront; that we keep in mind that what matters most is taking care of patients. I could not agree more and could not express it better. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Learn more about the technological future of medical specialties from \u003Ca href=\"https:\u002F\u002Fleanpub.com\u002Ffuture-of-medical-specialties\">our latest e-book\u003C\u002Fa>!\u003C\u002Fh3>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1920\" height=\"1080\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup.png\" alt=\"future of medical specialties\" class=\"wp-image-23819\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup.png 1920w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F05\u002F0415_tmfs_mockup-2048x1152.png 2048w\" sizes=\"auto, (max-width: 1920px) 100vw, 1920px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ctable style=\"width: 100%; border-collapse: collapse; background-color: #eee; border-top: 4px solid #444;\" cellpadding=\"10px\">\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd style=\"width: 100%;\">\n\u003Cp>\u003Cstrong>At The Medical Futurist, we are building a community for making a bold vision about the future of healthcare reality today.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ciframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FFIbMejImnxs\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen=\"\">\u003C\u002Fiframe>\n\u003Cp>If you’d like to support this mission, we invite you to \u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">join The Medical Futurist Patreon Community\u003C\u002Fa>. A community of empowered patients, future-oriented healthcare professionals, concerned health policymakers, sensible health tech developers, and enthusiastic medical students. If there were ever a time to join us, it is now. Every contribution, however big or small, powers our research and sustains our future.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">\u003Cstrong style=\"background-color: #e71d3299; color: #000;\">Click here to support The Medical Futurist from as little as $3\u003C\u002Fstrong>\u003C\u002Fa> – it only takes a minute. Thank you.\u003C\u002Fp>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\u003Cp> \u003C\u002Fp>\n",{"rendered":1974,"protected":16},"\u003Cp>Radiologists’ creative work will be necessary in the future to solve complex issues and supervising diagnostic processes; but AI will definitely become part of their daily routine in diagnosing simpler cases and taking over repetitive tasks. \u003C\u002Fp>\n",15922,{"_acf_changed":16,"footnotes":74},[350],[87,1979,1980,84,366,85,1981,1982,364,1983,1984,1985,365,1986,1987],327,372,519,163,628,271,708,282,289,[1077,92,372],[],[955,384,1991,1992,1993,257,1994,1995],1729,1783,1789,1883,2739,[1997,63,103,104,105,106,107,388,117,1998,1999,114,403,115,2000,2001,401,2002,2003,2004,402,2005,2006,1085,121,408],"post-15909","tag-mri","tag-radiology","tag-gc4","tag-cancer-2","tag-medical-imaging","tag-health","tag-ct-scanning","tag-ibm-watson","tag-innovation",{"id":1975,"alt_text":2008,"caption":74,"description":74,"media_type":124,"media_details":2009,"post":21,"source_url":2035},"Future of Radiology",{"width":2010,"height":2011,"file":2012,"sizes":2013,"image_meta":2033},870,532,"2017\u002F06\u002Ffuture-of-radiology-1.jpg",{"medium":2014,"large":2017,"thumbnail":2021,"medium_large":2024,"large_old_512x313":2025,"medium_old_409x250":2028},{"file":2015,"width":418,"height":419,"mime-type":542,"source_url":2016},"future-of-radiology-1-370x208.jpg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1-370x208.jpg",{"file":2018,"width":423,"height":2019,"mime-type":542,"source_url":2020},"future-of-radiology-1-768x470.jpg",470,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1-768x470.jpg",{"file":2022,"width":428,"height":428,"mime-type":542,"source_url":2023},"future-of-radiology-1-150x150.jpg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1-150x150.jpg",{"file":2018,"width":423,"height":2019,"mime-type":542,"source_url":2020},{"file":2026,"width":438,"height":87,"mime-type":542,"source_url":2027},"future-of-radiology-1-512x313.jpg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1-512x313.jpg",{"file":2029,"width":2030,"height":2031,"mime-type":542,"source_url":2032},"future-of-radiology-1-409x250.jpg",409,250,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1-409x250.jpg",{"aperture":163,"credit":74,"camera":74,"caption":74,"created_timestamp":163,"copyright":74,"focal_length":163,"iso":163,"shutter_speed":163,"title":74,"orientation":163,"keywords":2034},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F06\u002Ffuture-of-radiology-1.jpg",{"related_posts":16,"related_posts_footer":16,"cta_type":74,"cta_color":74,"subtitle":74,"related_books":16,"key_takeaways":2037},[2038,2040,2042],{"title":2039},"\u003Cp>What if an algorithm could tell you whether you have cancer based on your CT scan or mammography exam?\u003C\u002Fp>\n",{"title":2041},"\u003Cp>Radiologists’ creative work will be necessary in the future to solve complex issues and supervising diagnostic processes; but AI will definitely become part of their daily routine in diagnosing simpler cases and taking over repetitive tasks.\u003C\u002Fp>\n",{"title":2043},"\u003Cp>Rather than getting threatened by it, we should familiarize with how it could help change the course of radiology for the better.\u003C\u002Fp>\n",{"yoast_wpseo_title":2045,"yoast_wpseo_metadesc":2046,"yoast_wpseo_canonical":1968},"The Future of Radiology And Artificial Intelligence - The Medical Futurist","AI will become part of the daily routine of radiologists soon. So rather than getting threatened, we should understand how it changes its 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Guide to Artificial Intelligence in Healthcare",{"rendered":2103,"protected":16},"\n\u003Cp>Can we stay human in the\nage of A.I.? To go even further, can we grow in humanity, can we shape a\nmore humane, more equitable and sustainable healthcare?\u003C\u002Fp>\n\n\n\n\u003Cp>Our e-book aims to prepare\nhealthcare and medical professionals for the era of human-machine collaboration.\nRead The Medical Futurist’s guide to understanding, anticipating and\ncontrolling artificial intelligence.\u003C\u002Fp>\n",{"rendered":2105,"protected":16},"\u003Cp>Can we stay human in the age of A.I.? To go even further, can we grow in humanity, can we shape a more humane, more equitable 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