[{"data":1,"prerenderedAt":409},["ShallowReactive",2],{"slug-3-things-transhumanism-can-give-to-healthcare":3},{"post":4,"relatedPosts":172,"relatedBooks":314},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":6,"modified_gmt":7,"slug":10,"status":11,"type":12,"link":13,"title":14,"content":16,"excerpt":19,"author":21,"featured_media":22,"comment_status":23,"ping_status":23,"sticky":24,"template":25,"format":26,"meta":27,"categories":28,"tags":30,"project_category":32,"contact_email_category":35,"yst_prominent_words":36,"class_list":45,"better_featured_image":56,"acf":99,"yoast_meta":116,"_links":119},54271,"2026-07-14T09:34:53","2026-07-14T07:34:53",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=54271&_wpnonce=a7fadde38b&status=auto-draft&type=post","3-things-transhumanism-can-give-to-healthcare","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002F3-things-transhumanism-can-give-to-healthcare",{"rendered":15},"3 Things Transhumanism Can Give To Healthcare",{"rendered":17,"protected":18},"\n\u003Cp>Imagine a future where aging is not a fate but a solvable puzzle, reshaping the very fabric of medical science. This is what transhumanism aims for. Although this goal is surely too ambitious, we might learn a thing or two \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fsuperhumans\" target=\"_blank\" rel=\"noreferrer noopener\">from this futuristic movement\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What is transhumanism? \u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.sciencedirect.com\u002Ftopics\u002Fsocial-sciences\u002Ftranshumanism#:~:text=Transhumanism%20is%20the%20position%20that,capacities%20beyond%20current%20biological%20constraints\" target=\"_blank\" rel=\"noreferrer noopener\">Transhumanism is the position\u003C\u002Fa> that humans should be permitted to use technology to modify and enhance human cognition and bodily function, expanding abilities and capacities beyond current biological constraints. \u003C\u002Fp>\n\n\n\n\u003Cp>It is a philosophical and social movement, with not only technological aspirations. It is also an approach to exploring how advancements in science and technology could fundamentally transform human life. It has several key aspects: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Human enhancement\u003C\u002Fstrong>: this involves the use of technologies like genetic engineering, brain-computer interfaces, and nanotechnology to enhance human intelligence, physical strength, and lifespan. Ironically, all the trivial pop cultural references, like Darth Vader or the Terminator are discouraging. So let’s think about Ironman here.  \u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Life extension\u003C\u002Fstrong>: transhumanists often focus on extending human life significantly, potentially to immortality. This could be achieved through methods like anti-aging technologies, regenerative medicine, and possibly in the future, mind uploading.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Ethical considerations\u003C\u002Fstrong>: transhumanism raises various ethical questions, such as the potential for widening social inequalities, the nature of human identity and rights in the context of enhanced individuals, and the possible risks of advanced technologies. It also challenges current medical and ethical norms, prompting a reevaluation of what it means to be human.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>A few years ago \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fzoltan-istvan-and-the-jesus-singularity\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">we had an interview with the U.S. presidential candidate\u003C\u002Fa> of the Transhumanist party, explaining their visions in great detail. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>1. Fighting for rights that don’t even exist today \u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>One of the things transhumanism can give to medicine is that it can help us fight for rights that are maybe even nonexistent or unnecessary today but will be needed in the future as technology advances. Just as the internet gave rise to digital privacy rights, transhumanism will bring forth rights we haven’t even thought about yet.\u003C\u002Fp>\n\n\n\n\u003Cp>Like rights related to our robotics and\u002For AI-enhanced bodies. The question arises: what rights do individuals have when part of their cognitive processes or physical abilities are enhanced or even controlled by AI? It’s like asking who gets to decide what your smart prosthetic arm can or can’t do.\u003C\u002Fp>\n\n\n\n\u003Cp>Similarly, the rights of biohackers. These are the pioneers, often working outside of traditional labs, who experiment with biology and technology to push the boundaries of human capabilities. But here’s the thing: as they experiment with their own bodies, they challenge existing medical and legal frameworks. They are DIY enthusiasts, but instead of building birdhouses, they’re building – hopefully – better versions of themselves. What rights do these innovators have (or don’t have?), and how do we ensure their safety without stifling their creativity? Where are the boundaries of their freedom? Where are the boundaries of our obligations to protect humans with societal-level safeguards?\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\u002F11\u002Ftmf_article_392_nanobots-768x432.png\" alt=\"\" class=\"wp-image-53803\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F11\u002Ftmf_article_392_nanobots-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F11\u002Ftmf_article_392_nanobots-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F11\u002Ftmf_article_392_nanobots-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F11\u002Ftmf_article_392_nanobots-2048x1152.png 2048w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>In the future, we’ll likely need a whole new set of rights and ethical guidelines tailored to a world where humans and technology are intertwined. It’s not just about who gets access to these technologies, but also about maintaining autonomy and individuality in a world where we might be part biological, part machine.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>2. Mapping out feasible innovations for disease management\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Bryan Johnson’s venture into transhumanism is a vivid illustration of the extremes to which individuals might go in pursuit of longevity and enhanced health. Spending 2 million dollars per year, his lifestyle embodies a radical approach to pushing the human body’s boundaries. While this level of investment is far from feasible for the average person, Johnson’s project could yield valuable insights.\u003C\u002Fp>\n\n\n\n\u003Cp>Scientists and medical professionals could potentially validate and replicate findings from his extensive personal health experiments. This aspect is crucial: while not everyone can emulate Johnson’s lifestyle, the knowledge gained could inform more accessible health strategies.\u003C\u002Fp>\n\n\n\n\u003Cp>What Johnson does can help us figure out what things we should consider implementing and what not. For example: sitting for two hours in blue light every single evening might not be worth the effort. You might sleep perfectly well with a consistent sleep routine and several simple measures regarding your exercise habits, eating habits, and caffeine consumption as I do or Dr. Mesko does. \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\u002F12\u002F226_tmf-01-768x432.png\" alt=\"Withings ScanWatch review\" class=\"wp-image-31481\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F12\u002F226_tmf-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F12\u002F226_tmf-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F12\u002F226_tmf-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F12\u002F226_tmf-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Projects like Johnson’s “Blueprint” are on the fringe of current medical practice, they offer a glimpse into the potential extremes of human enhancement. However, the lessons learned from such endeavors can guide more practical, everyday approaches to health and longevity that are accessible to the broader population. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>3. Is it for all? Is it for the wealthy?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Transhumanism can also help us figure out how to address concerns about inequality, particularly the potential for technologies to favor the wealthy. Technologies, such as genetic modifications, neural enhancements, or anti-aging therapies, are likely to be expensive, at least initially. This raises the question: if only the wealthy can afford these enhancements, does it create a society where the rich can buy better health, longevity, and even intelligence, widening the gap between the rich and the poor?\u003C\u002Fp>\n\n\n\n\u003Cp>We \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhealth-equity-in-the-ai-and-digital-health-era-promise-or-peril\u002F\" target=\"_blank\">are already struggling\u003C\u002Fa> with \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-widening-gap-in-access-to-healthcare-between-rich-and-poor-can-only-be-bridged-with-digital-health-solutions-if-they-are-used-wisely\u002F\" target=\"_blank\">this dilemma\u003C\u002Fa> in digital health, with wearables and personalised medicine, but how extreme can it become? There’s a concern that transhumanism could lead to a new class divide – between those who are enhanced and those who are not. This could manifest not just in terms of health and lifespan, but also in areas like employment, where enhanced individuals might have unfair advantages.\u003C\u002Fp>\n\n\n\n\u003Cp>As with other health-inequity issues, one of the core debates in transhumanism is whether its benefits will trickle down to the wider society or remain exclusive to those who can afford them.  To address these concerns, there is a growing discussion among ethicists, policymakers, and transhumanists themselves about how to ensure equitable access to these technologies. This includes considering regulations, subsidies, and ethical guidelines to prevent the deepening of social inequalities. \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\u002F02\u002Ftmf_article_243-01-768x432.png\" alt=\"\" class=\"wp-image-32629\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Evidence-based implementation\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Diving into the realm of transhumanism and its profound implications for the future of healthcare can be fascinating. However, one principle remains paramount: we need an evidence-based approach. \u003C\u002Fp>\n\n\n\n\u003Cp>Whether it’s about embracing new technologies, innovative treatments, or regulatory changes, the transition from transhumanist theory to healthcare application must be grounded in solid, scientific evidence. This is a critical understanding that the transhumanist community must also embrace.\u003C\u002Fp>\n\n\n\n\u003Cp>The healthcare world is inherently cautious, prioritizing patient safety and proven effectiveness. For transhumanist innovations to gain acceptance and integration into mainstream medical practice, they must undergo rigorous testing and validation. This process ensures that these advancements are not only scientifically sound but also ethically responsible and beneficial to patients.\u003C\u002Fp>\n",false,{"rendered":20,"protected":18},"\u003Cp>Transhumanisms dreams of a future where aging is not a fate but a solvable puzzle. This futuristic movement sheds light on new rights, maps out feasible innovations for disease management, and addresses the ethical dilemma of accessibility. But we need evidence.\u003C\u002Fp>\n",6,54283,"closed",true,"","standard",{"_acf_changed":18,"footnotes":25},[29],7079,[31],1332,[33,34],950,951,[],[37,38,39,40,41,42,43,44],1571,1719,1721,1723,2017,3347,4067,5717,[46,12,47,48,49,50,51,52,53,54,55],"post-54271","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","tag-transhumanism","project_category-medical-professionals","project_category-patients",{"id":22,"alt_text":25,"caption":25,"description":25,"media_type":57,"media_details":58,"post":5,"source_url":98},"image",{"width":59,"height":60,"file":61,"filesize":62,"sizes":63,"image_meta":95},6667,3750,"2023\u002F12\u002Ftmf_article_395.png",582413,{"medium":64,"large":71,"thumbnail":77,"medium_large":82,"1536x1536":83,"2048x2048":89},{"file":65,"width":66,"height":67,"mime-type":68,"filesize":69,"source_url":70},"tmf_article_395-370x208.png",370,208,"image\u002Fpng",25834,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395-370x208.png",{"file":72,"width":73,"height":74,"mime-type":68,"filesize":75,"source_url":76},"tmf_article_395-768x432.png",768,432,61910,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395-768x432.png",{"file":78,"width":79,"height":79,"mime-type":68,"filesize":80,"source_url":81},"tmf_article_395-150x150.png",150,14114,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395-150x150.png",{"file":72,"width":73,"height":74,"mime-type":68,"filesize":75,"source_url":76},{"file":84,"width":85,"height":86,"mime-type":68,"filesize":87,"source_url":88},"tmf_article_395-1536x864.png",1536,864,142203,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395-1536x864.png",{"file":90,"width":91,"height":92,"mime-type":68,"filesize":93,"source_url":94},"tmf_article_395-2048x1152.png",2048,1152,202166,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395-2048x1152.png",{"aperture":96,"credit":25,"camera":25,"caption":25,"created_timestamp":96,"copyright":25,"focal_length":96,"iso":96,"shutter_speed":96,"title":25,"orientation":96,"keywords":97},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_395.png",{"cta_type":100,"cta_color":25,"related_books":101,"related_posts_footer":105,"related_posts":18,"subtitle":25,"key_takeaways":109},"subscribe",[102,103,104],52203,47427,30419,[106,107,108],54095,13949,27125,[110,112,114],{"title":111},"\u003Cp>While transhumanism often ventures into the realm of the futuristic, it offers important lessons that can shape our approach to healthcare and human enhancement.\u003C\u002Fp>\n",{"title":113},"\u003Cp>Transhumanism highlights areas where excessive investment may and may not be worthwhile, guiding us toward more effective and practical health interventions.\u003C\u002Fp>\n",{"title":115},"\u003Cp>Only through an evidence-based approach can transhumanist innovations be responsibly and effectively integrated into the field of medicine, ensuring patient safety and real-world applicability.\u003C\u002Fp>\n",{"yoast_wpseo_title":117,"yoast_wpseo_metadesc":118,"yoast_wpseo_canonical":13},"3 Things Transhumanism Can Give To Healthcare - The Medical Futurist","Transhumanisms dreams of a future where aging is not a fate but a solvable puzzle. This movement may upgrade disease management, but we need evidence.",{"self":120,"collection":126,"about":129,"author":132,"replies":135,"version-history":138,"predecessor-version":142,"wp:featuredmedia":146,"wp:attachment":149,"wp:term":152,"curies":168},[121],{"href":122,"targetHints":123},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54271",{"allow":124},[125],"GET",[127],{"href":128},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[130],{"href":131},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[133],{"embeddable":24,"href":134},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[136],{"embeddable":24,"href":137},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=54271",[139],{"count":140,"href":141},17,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54271\u002Frevisions",[143],{"id":144,"href":145},54327,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54271\u002Frevisions\u002F54327",[147],{"embeddable":24,"href":148},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F54283",[150],{"href":151},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=54271",[153,156,159,162,165],{"taxonomy":154,"embeddable":24,"href":155},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=54271",{"taxonomy":157,"embeddable":24,"href":158},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=54271",{"taxonomy":160,"embeddable":24,"href":161},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=54271",{"taxonomy":163,"embeddable":24,"href":164},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=54271",{"taxonomy":166,"embeddable":24,"href":167},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=54271",[169],{"name":170,"href":171,"templated":24},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[173],{"id":108,"date":174,"date_gmt":175,"guid":176,"modified":178,"modified_gmt":179,"slug":180,"status":11,"type":12,"link":181,"title":182,"content":184,"excerpt":186,"author":188,"featured_media":189,"comment_status":23,"ping_status":23,"sticky":24,"template":25,"format":26,"meta":190,"categories":191,"tags":193,"project_category":200,"contact_email_category":202,"yst_prominent_words":203,"class_list":215,"better_featured_image":225,"acf":255,"yoast_meta":268,"_links":271},"2025-04-07T10:00:00","2025-04-07T08:00:00",{"rendered":177},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=27125&_wpnonce=5f715b0750&status=auto-draft&type=post","2025-04-03T15:56:50","2025-04-03T13:56:50","the-curious-case-of-a-i-discovering-unusual-associations-in-medicine","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-curious-case-of-a-i-discovering-unusual-associations-in-medicine",{"rendered":183},"AI’s Unforeseen Medical Discoveries: The Curious Case Of Unusual Associations",{"rendered":185,"protected":18},"\n\u003Cp>Artificial intelligence (AI) can do \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhats-next-for-ai-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">a plethora of astonishing things\u003C\u002Fa> in the medical space, from automating triage and administrative tasks to assisting in mental health support and medical image analysis. On top of these, every now and then, AI makes curious medical discoveries, detecting things that – to the best of our human knowledge – should not be detectable from the input data. \u003C\u002Fp>\n\n\n\n\u003Cp>These unusual associations present brand-new challenges to medical professionals who need to better understand how smart algorithms come to such conclusions that have eluded humans for decades. In this article, we consider some striking examples of AI finding connections that would otherwise remain invisible to human experts. Such observations highlight the technology’s potential and how it will continue to surprise us in the years to come.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Debiasing and speeding up radiological imaging\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>With \u003Ca href=\"https:\u002F\u002Fwww.mcpdigitalhealth.org\u002Farticle\u002FS2949-7612(24)00121-4\u002Ffulltext\" target=\"_blank\" rel=\"noreferrer noopener\">the majority of FDA-approved medical AI tools\u003C\u002Fa> targeted at radiological use, it is not surprising that the technology has found unusual associations in this field.\u003C\u002Fp>\n\n\n\n\u003Cp>In an interesting study, MIT scientists showed that deep learning algorithms \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnews.mit.edu\u002F2022\u002Fartificial-intelligence-predicts-patients-race-from-medical-images-0520\" target=\"_blank\">can predict\u003C\u002Fa> the self-reported race of patients from radiological images alone. This is a feat even the most seasoned physicians cannot do, and it’s not clear how the model was able to do this. Such insights can have practical uses as they help to \u003Ca href=\"https:\u002F\u002Fnews.mit.edu\u002F2022\u002Fartificial-intelligence-predicts-patients-race-from-medical-images-0520\" target=\"_blank\" rel=\"noreferrer noopener\">counter bias\u003C\u002Fa> inherent in medical records.\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\u002F2019\u002F08\u002Ftmf_article_350-01_2_720.png\" alt=\"TMF AU doctor algorithm radiology digital health\" class=\"wp-image-48905\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F08\u002Ftmf_article_350-01_2_720.png 720w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F08\u002Ftmf_article_350-01_2_720-370x208.png 370w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>At UMass Memorial Health, \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">at least 40 AI tools\u003C\u002Fa> assist in clinical workflows, handling tasks such as getting results to critical patients faster and assisting in billing. They also aid in refining the quality of radiological images. This has been associated with patients spending less time in MRI machines. The scanning process is thus made more tolerable and patients feel less anxious.\u003C\u002Fp>\n\n\n\n\u003Cp>“MRIs are long, uncomfortable and loud, but they’re really valuable for medical decision making,” Dr. Elisabeth Garwood from UMass Memorial Health \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">explained\u003C\u002Fa>. “The acceleration algorithms at UMass are making our MRIs 25 percent faster, and that really hacks the patient experience that they’re in the MRI for less time.”\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Enhancing diagnoses with photos, voice recordings and breath scans\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In the digital health market, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-do-digital-biomarkers-mean\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">digital biomarkers\u003C\u002Fa>, or digital data that provide insights into an individual’s health status, are gaining popularity, but AI seem to be able to derive insights from its own unusual sources.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers \u003Ca href=\"https:\u002F\u002Fwww.mcpdigitalhealth.org\u002Farticle\u002FS2949-7612(23)00073-1\u002Ffulltext\" target=\"_blank\" rel=\"noreferrer noopener\">trained a model\u003C\u002Fa> to analyse 10-second-long voice recordings to diagnose type 2 diabetes based on certain acoustic features. While not displaying ideal performance, the model produced promising results, which were better than chance in correctly identifying diabetic individuals. This development makes the scenario of being able to detect one’s blood glucose levels from a smartphone quite plausible.\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\u002F11\u002Ftmf_article_305-01-1-768x432.png\" alt=\"vocal biiomarker, TMF, digital health\" class=\"wp-image-36955\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Dr. Jude Kong, who leads the Africa-Canada AI & Data Innovation Consortium and the Global South AI for Pandemic & Epidemic Preparedness & Response Network, has been collaborating with governments to \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">employ bespoke AI tools for practical diagnoses\u003C\u002Fa> through unconventional means. \u003C\u002Fp>\n\n\n\n\u003Cp>For example, a model deployed in Ethiopia can help determine if a patient’s paralysis is indicative of polio based on a photograph. In Peru, they co-created a breathalyzer that leverages AI technology to help diagnose respiratory disease.\u003C\u002Fp>\n\n\n\n\u003Cp>Google researchers also employed AI to detect health risks from images. In particular, they \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41551-018-0195-0\" target=\"_blank\" rel=\"noreferrer noopener\">trained deep-learning models\u003C\u002Fa> to identify signs indicating long-term cardiovascular risks from retinal images.\u003C\u002Fp>\n\n\n\n\u003Cp>Traditionally, in order to assess those risks, doctors need to manually look at the retina, do blood tests and consider other factors like age and BMI. Impressively, \u003Ca href=\"https:\u002F\u002Fwww.washingtonpost.com\u002Fnews\u002Fthe-switch\u002Fwp\u002F2018\u002F02\u002F19\u002Fgoogle-used-artificial-intelligence-to-predict-heart-attacks-with-the-human-eye\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">the AI taught itself what to look for\u003C\u002Fa> in retinal images alone after having gone through enough data to identify patterns found in the eyes of people at risk.\u003C\u002Fp>\n\n\n\n\u003Cp>Such technology can prove to be lifesaving, especially considering the fact that \u003Ca href=\"https:\u002F\u002Fwww.who.int\u002Fhealth-topics\u002Fcardiovascular-diseases\" target=\"_blank\" rel=\"noreferrer noopener\">some 17 million people die of cardiovascular diseases\u003C\u002Fa> every year. It can help doctors and even patients run a quick screening test and assess their risk and take subsequent preventive actions.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Improving psychiatric care with brain waves, early Alzheimer’s detection and coma recovery assessments\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Psychiatric care stands to gain a boost thanks to the assistance of AI. As surprising as it might sound, treatment selection for antidepressants is \u003Ca href=\"https:\u002F\u002Ftime.com\u002F5786081\u002Fdepression-medication-treatment-artificial-intelligence\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">generally based on\u003C\u002Fa> trial and error. This is the reason that \u003Ca href=\"https:\u002F\u002Fajp.psychiatryonline.org\u002Fdoi\u002F10.1176\u002Fappi.ajp.163.1.5\" target=\"_blank\" rel=\"noreferrer noopener\">only 30% of patients\u003C\u002Fa> respond well to the first antidepressant prescribed, but the input of AI can provide a more effective method. \u003C\u002Fp>\n\n\n\n\u003Cp>By studying the brainwaves of patients, researchers \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41587-019-0397-3#author-information\" target=\"_blank\" rel=\"noreferrer noopener\">used a machine learning algorithm\u003C\u002Fa> to identify the best antidepressant: sertaline, in this case. Their results showed that 65% of patients with a particular brainwave pattern indicated a strong response to sertraline. One of the researchers suggested that this method is “far better” than relying on clinical factors, such as certain symptoms, to try to guess whether a drug will have a favourable effect on patients.\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>For a condition like Alzheimer’s, patients are commonly diagnosed with the condition after the symptoms manifest. These can be very debilitating, such as memory loss, personality changes and depression. A research team at the University of California in San Francisco trained an algorithm to look for indicative signs of Alzheimer’s from another angle.\u003C\u002Fp>\n\n\n\n\u003Cp>The researchers \u003Ca href=\"https:\u002F\u002Fmedicalxpress.com\u002Fnews\u002F2018-11-artificial-intelligence-alzheimer-years-diagnosis.html\" target=\"_blank\" rel=\"noreferrer noopener\">trained a deep learning algorithm on FDG-PET scans\u003C\u002Fa>, a method used to study the metabolic activity of brain cells. This taught the AI to recognise metabolic patterns associated with Alzheimer’s disease. In subsequent tests, the AI detected the condition with 100% sensitivity, on average more than six years prior to the final diagnosis!\u003C\u002Fp>\n\n\n\n\u003Cp>Being in a coma or vegetative state can be one of the most ethically-taxing issues in healthcare. Based on doctors’ recommendations, relatives of such patients can decide if they would like to terminate life support. It’s a highly debatable issue what the decision will prolong: the patient’s life or suffering, while also costing both the relatives and the healthcare system. However, AI can aid in making more informed decisions in these cases, correctly predicting if one will regain consciousness even after doctors conclude an unlikely recovery.\u003C\u002Fp>\n\n\n\n\u003Cp>Such an AI system has been developed by the Chinese Academy of Sciences and PLA General Hospital in Beijing. Their algorithm \u003Ca href=\"https:\u002F\u002Fwww.scmp.com\u002Fnews\u002Fchina\u002Fscience\u002Farticle\u002F2163298\u002Fdoctors-said-coma-patients-would-never-wake-ai-said-they-would\" target=\"_blank\" rel=\"noreferrer noopener\">reportedly achieved about 90 percent accuracy\u003C\u002Fa> on prognostic assessments. The software analyzes brain scans to re-evaluate doctor’s decisions. In at least 7 cases where doctors were confident that patients wouldn’t regain consciousness, the AI contradicted them and indeed those patients woke up within 12 months of the brain scans. “Our machine can ‘see’ things invisible to human eyes,” \u003Ca href=\"https:\u002F\u002Fwww.scmp.com\u002Fnews\u002Fchina\u002Fscience\u002Farticle\u002F2163298\u002Fdoctors-said-coma-patients-would-never-wake-ai-said-they-would\" target=\"_blank\" rel=\"noreferrer noopener\">Dr Song Ming, first author of the study, said\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>This is because the evaluation of patients is done using a brain scan with functional magnetic resonance imaging and the rapidly evolving neural activities can prove challenging for doctors to detect. On the other hand, a machine learning algorithm can detect minute changes indicative of an ongoing recovery. This could help doctors and relatives make more informed decisions when it comes to such patients.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Aiding the identification and treatment of rare diseases\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>If a disease is rare, then its identification and treatment will pose a challenge. Yearly, about half a million children are born with a rare hereditary disease around the world. However, many of these cases present with specific physical features that can help in their identification. Clinicians might miss these due to the fact that they’ve never seen such cases. In addition, due to the rarity of such cases, treatment options are often poorly understood. However, nothing escapes the meticulous eye of AI.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers from the University of Pennsylvania used a predictive AI tool to identify a suitable medicine to \u003Ca href=\"https:\u002F\u002Fwww.pennmedicine.org\u002Fnews\u002Fnews-releases\u002F2025\u002Ffebruary\u002Fai-tool-helps-find-life-saving-medicine-for-rare-disease\" target=\"_blank\" rel=\"noreferrer noopener\">save the life of a patient\u003C\u002Fa> with idiopathic multicentric Castleman’s disease (iMCD). This rare condition is characterised by a poor survival rate and a lack of treatment. \u003C\u002Fp>\n\n\n\n\u003Cp>But after analysing thousands of existing medications, the AI system predicted that an FDA-approved monoclonal antibody used to treat other conditions would likely work for iMCD; and it did. The patient is now almost two years into remission, and this approach could also be applicable to other rare diseases.\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\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\u003C\u002Fdiv>\n\n\n\u003Cp>Researchers based in Germany \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41436-019-0566-2\" target=\"_blank\" rel=\"noreferrer noopener\">developed and trained an algorithm\u003C\u002Fa> to help the identification of diseases caused by a change in a single gene. These include conditions like mucopolysaccharidosis, Mabry syndrome and Kabuki syndrome, where those affected have characteristic facial features.\u003C\u002Fp>\n\n\n\n\u003Cp>The researchers trained the neural network DeepGestalt with 30,000 portrait photos of those with such rare conditions. “In combination with facial analysis, it is possible to filter out the decisive genetic factors and prioritize genes,” \u003Ca href=\"https:\u002F\u002Fwww.sciencedaily.com\u002Freleases\u002F2019\u002F06\u002F190606133805.htm\" target=\"_blank\" rel=\"noreferrer noopener\">said Prof. Krawitz\u003C\u002Fa> who worked on this study. “Merging data in the neuronal network reduces data analysis time and leads to a higher rate of diagnosis.”\u003C\u002Fp>\n\n\n\n\u003Cp>Their results showed that with the help of AI, identifying rare diseases was much more accurate. Using this technique could fast-track the identification and treatment of those affected from early on.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Synchronising surgical rooms\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>While there is a promising \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-technological-future-of-surgery\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">technological future of surgery\u003C\u002Fa>, the focus is mostly on assisting surgeons instead of the whole surgical team working behind the scenes of procedures.  To enhance the collaboration and synchronicity of surgical teams, \u003Ca href=\"https:\u002F\u002Fexex.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">startup eXeX\u003C\u002Fa> has developed a dedicated AI platform. It leverages the Apple Vision Pro headset to improve communication, clarity and orientation within the surgical suite.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png\" alt=\"\" class=\"wp-image-34403\" width=\"768\" height=\"432\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Their product combines a language model with a computer vision model to assist the surgical teams in answering questions during a procedure and help them orient themselves in the room. \u003C\u002Fp>\n\n\n\n\u003Cp>“The app running on the headset has a full spatial awareness in the room in real time, and it understands exactly where the user is and even knows what the user is looking at,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fexex.ai\u002F\" target=\"_blank\">explained Nicholas Cambata\u003C\u002Fa>, COO of eXeX. For example, a surgical assistant could set up a tray prior to a procedure and request a check from the AI. The tool can identify any missing equipment and guide the user to the exact location in the room.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Points system to assess one’s need for hospitalization\u003C\u002Fh2>\n\n\n\n\u003Cp>This was the premise of \u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\">a pilot \u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">p\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\">roject\u003C\u002Fa> from Bering Research and GPs at Axbridge Surgery in Somerset, England. An algorithm was deployed to predict which patients might need to be admitted to a hospital and to help GPs work on reducing the risk.\u003C\u002Fp>\n\n\n\n\u003Cp>The AI allocates points, based on a percentage scale, according to underlying health conditions and contributing factors like elevated blood pressure or smoking habits. The higher the points, the more likely the patient will need hospitalization.\u003C\u002Fp>\n\n\n\n\u003Cp>The aim is to have GPs intervene earlier, make accurate predictions on hospital admissions, and help hospitals plan on allocating their resources.\u003C\u002Fp>\n\n\n\n\u003Cp>While these unusual associations give a glimmer of hope to millions of patients around the world, we must be cautious about how we take this news. The experiments conducted need to be validated and repeated on a larger scale while considering other contributing factors like comorbidities.\u003C\u002Fp>\n\n\n\n\u003Cp>However, it does show that artificial intelligence can become an integral part of not only treating patients but also identifying risks, and taking preventive measures we have never thought about before.\u003C\u002Fp>\n",{"rendered":187,"protected":18},"\u003Cp>Determining patients’ race from chest x-rays alone or diagnosing type 2 diabetes from short audio samples. AI can do it and we don’t know how. There are fascinating examples of unusual associations.\u003C\u002Fp>\n",16,27237,{"_acf_changed":18,"footnotes":25},[29,192],504,[194,195,196,197,198,199],207,275,313,425,134,144,[201,33,34],949,[],[204,205,206,207,208,209,210,211,212,213,214],1789,1833,2717,2719,2737,2741,2747,2755,1587,1631,1715,[216,12,47,48,49,50,51,52,217,218,219,220,221,222,223,224,54,55],"post-27125","category-artificial-intelligence","tag-digital-health","tag-healthcare","tag-medicine","tag-technology-2","tag-ai","tag-artificial-intelligence","project_category-educators",{"id":189,"alt_text":226,"caption":25,"description":25,"media_type":57,"media_details":227,"post":108,"source_url":254},"AI association",{"width":228,"height":229,"file":230,"sizes":231,"image_meta":253},1920,1080,"2020\u002F03\u002FAI-association-small.jpg",{"medium":232,"large":238,"thumbnail":243,"medium_large":247,"1536x1536":248},{"file":233,"width":234,"height":235,"mime-type":236,"source_url":237},"AI-association-small-370x208.jpg","370","208","image\u002Fjpeg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-370x208.jpg",{"file":239,"width":240,"height":241,"mime-type":236,"source_url":242},"AI-association-small-768x432.jpg","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-768x432.jpg",{"file":244,"width":245,"height":245,"mime-type":236,"source_url":246},"AI-association-small-150x150.jpg","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-150x150.jpg",{"file":239,"width":240,"height":241,"mime-type":236,"source_url":242},{"file":249,"width":250,"height":251,"mime-type":236,"source_url":252},"AI-association-small-1536x864.jpg","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-1536x864.jpg",{"aperture":96,"credit":25,"camera":25,"caption":25,"created_timestamp":96,"copyright":25,"focal_length":96,"iso":96,"shutter_speed":96,"title":25,"orientation":96},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small.jpg",{"cta_type":100,"cta_color":25,"subtitle":25,"related_books":256,"related_posts_footer":259,"related_posts":18,"key_takeaways":263},[257,258,102],24762,24761,[260,261,262],53645,53187,52901,[264,266],{"title":265},"\u003Cp>Artificial intelligence has wide-ranging applications in medical practice, but the technology continues to surprise in novel ways.\u003C\u002Fp>\n",{"title":267},"\u003Cp>In this article, we uncover some unusual medical associations made with AI that would otherwise remain oblivious to human eyes.\u003C\u002Fp>\n",{"yoast_wpseo_title":269,"yoast_wpseo_metadesc":270,"yoast_wpseo_canonical":181},"AI's Unforeseen Medical Discoveries: Unusual Associations","AI has amazing medical discoveries, and sometimes we don't know how it came to the correct results as the input data seems insufficient for 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