[{"data":1,"prerenderedAt":631},["ShallowReactive",2],{"infographic-fda-approved-ai-based-medical-devices":3},{"infographic":4,"related":126},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":26,"class_list":27,"better_featured_image":33,"acf":76,"yoast_meta":90,"_links":92},51091,"2023-05-26T13:57:12","2023-05-26T11:57:12",{"rendered":9},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=51091","2023-05-26T13:57:14","2023-05-26T11:57:14","fda-approved-ai-based-medical-devices","publish","infographic","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Ffda-approved-ai-based-medical-devices\u002F",{"rendered":17},"FDA-Approved AI-Based Medical Devices",{"rendered":19,"protected":20},"",false,{"rendered":22,"protected":20},"\u003Cp>This infographic is based on the official list of the FDA and displays the medical fields, types of submissions, and final decision dates all in one place.\u003C\u002Fp>\n",6,51093,"closed",[],[28,14,29,30,31,32],"post-51091","type-infographic","status-publish","has-post-thumbnail","hentry",{"id":24,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":35,"post":5,"source_url":75},"image",{"width":36,"height":37,"file":38,"filesize":39,"sizes":40,"image_meta":72},1920,2113,"2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices.png",902068,{"medium":41,"large":48,"thumbnail":54,"medium_large":59,"1536x1536":60,"2048x2048":66},{"file":42,"width":43,"height":44,"mime-type":45,"filesize":46,"source_url":47},"0420_FDA-Approved-AI-Based-Medical-Devices-370x208.png",370,208,"image\u002Fpng",45489,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices-370x208.png",{"file":49,"width":50,"height":51,"mime-type":45,"filesize":52,"source_url":53},"0420_FDA-Approved-AI-Based-Medical-Devices-768x845.png",768,845,238143,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices-768x845.png",{"file":55,"width":56,"height":56,"mime-type":45,"filesize":57,"source_url":58},"0420_FDA-Approved-AI-Based-Medical-Devices-150x150.png",150,23788,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices-150x150.png",{"file":49,"width":50,"height":51,"mime-type":45,"filesize":52,"source_url":53},{"file":61,"width":62,"height":63,"mime-type":45,"filesize":64,"source_url":65},"0420_FDA-Approved-AI-Based-Medical-Devices-1396x1536.png",1396,1536,505600,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices-1396x1536.png",{"file":67,"width":68,"height":69,"mime-type":45,"filesize":70,"source_url":71},"0420_FDA-Approved-AI-Based-Medical-Devices-1861x2048.png",1861,2048,716214,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices-1861x2048.png",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":74},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002F0420_FDA-Approved-AI-Based-Medical-Devices.png",{"related_article":77},{"ID":78,"post_author":79,"post_date":80,"post_date_gmt":81,"post_content":82,"post_title":83,"post_excerpt":84,"post_status":13,"comment_status":25,"ping_status":25,"post_password":19,"post_name":85,"to_ping":19,"pinged":19,"post_modified":80,"post_modified_gmt":81,"post_content_filtered":19,"post_parent":86,"guid":87,"menu_order":86,"post_type":88,"post_mime_type":19,"comment_count":73,"filter":89},22987,"6","2025-11-27 13:33:46","2025-11-27 12:33:46","\u003C!-- wp:paragraph -->\n\u003Cp>As artificial intelligence (AI) tools have been invading more or less every area of healthcare, we made a list to keep track of the top AI algorithms aiming for better diagnostics, more sophisticated patient care or further sighted predictions of diseases.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Does AI beat doctors?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Only if you have lived under a rock for the last couple of years could you not have heard about artificial intelligence and the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fartificial-intelligence-will-redesign-healthcare\" target=\"_blank\">potential of AI in healthcare\u003C\u002Fa>. \u003Cstrong>Not only smart algorithms themselves but also the \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-does-gpt-4-mean-for-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">hype around AI\u003C\u002Fa> has grown immensely, thus every time a new study about deep learning or machine learning in diagnostics, medical imaging or any other medical field gets published, newsreaders can be sure that some titles will say that “\u003Cem>\u003Ca href=\"https:\u002F\u002Fcardiovascularbusiness.com\u002Ftopics\u002Fcardiac-imaging\u002Fechocardiography\u002Fcardiologists-find-ai-be-more-accurate-sonographers-interpreting-echocardiograms\" target=\"_blank\" rel=\"noreferrer noopener\">AI\u003C\u002Fa> has \u003Ca href=\"https:\u002F\u002Fwww.medpagetoday.com\u002Fspecial-reports\u002Fexclusives\u002F103522\" target=\"_blank\" rel=\"noreferrer noopener\">again \u003C\u002Fa>beaten \u003Ca href=\"https:\u002F\u002Fwww.bbc.com\u002Fnews\u002Fhealth-50857759\" target=\"_blank\" rel=\"noreferrer noopener\">doctors\u003C\u002Fa> in \u003Ca href=\"https:\u002F\u002Fwww.insideprecisionmedicine.com\u002Ftopics\u002Fpatient-care\u002Fear-disorders\u002Fai-better-than-doctors-at-diagnosing-pediatric-ear-infections\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">field X\u003C\u002Fa>\u003C\u002Fem>”\u003C\u002Fstrong>. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The narrative is so distorted towards extreme visions that artificial intelligence is either presented as the ultimate evil destroying mankind – both \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=B-Osn1gMNtw\" target=\"_blank\">Elon Musk\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.bbc.com\u002Fnews\u002Ftechnology-30290540\" target=\"_blank\">Stephen Hawking\u003C\u002Fa> warned about that years ago - or the only source of the future prosperity of humanity. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Just think of the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftechcrunch.com\u002F2023\u002F03\u002F28\u002F1100-notable-signatories-just-signed-an-open-letter-asking-all-ai-labs-to-immediately-pause-for-at-least-6-months\u002F?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAKmu7s0KQrRwyPz-pZWYbtBvxSfTZel6Bhu79sE47N0ZiTHa8J8dgD0cpbPzxWkUDxqHzo4b8Kmm_vdp9C8AksGAcAa1tGtZTulyeb_ErIP9rg_WbwQYPX1diD78X2bwWJ6Q9jYS_j0UWxGpe-Ryaz9gaJfohEA_9UcTtCvGpK3n\" target=\"_blank\">open letter conundrum\u003C\u002Fa> of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs42256-023-00649-x\" target=\"_blank\">recent weeks\u003C\u002Fa>, and how fears of the general population were fueled despite the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fventurebeat.com\u002Fai\u002Ftitans-of-ai-industry-andrew-ng-and-yann-lecun-oppose-call-for-pause-on-powerful-ai-systems\u002F\" target=\"_blank\">opposing opinions\u003C\u002Fa> of the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Ftechnology\u002Fbill-gates-says-calls-pause-ai-wont-solve-challenges-2023-04-04\u002F\" target=\"_blank\">largest minds\u003C\u002Fa> calling for a more nuanced approach. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>By enumerating the top AI tools that we discovered in healthcare so far, we also aim to add what we believe is already useful for the work of medical professionals.\u003C\u002Fstrong> \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":50547,\"width\":\"960px\",\"height\":\"540px\",\"sizeSlug\":\"full\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-full is-resized\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357.png\" alt=\"TMF, medical student, AI, doctor, data, computer\" class=\"wp-image-50547\" style=\"width:960px;height:540px\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Life is no training data set\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Artificial intelligence \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fastcompany.com\u002F90863983\u002Fchatgpt-medical-diagnosis-emergency-room?utm_source=The+Medical+Futurist+Newsletter&utm_campaign=872032dc60-EMAIL_CAMPAIGN_2022_02_01_COPY_01&utm_medium=email&utm_term=0_efd6a3cd08-872032dc60-420889096&mc_cid=872032dc60&mc_eid=b5d5d75ed3\" target=\"_blank\">has numerous limitations\u003C\u002Fa> just as yet, so before we present our list, it’s worth going through them one by one. Already the term is misleading as AI implies a far more developed technology where it is standing at the moment. At best, current science – meaning \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\" target=\"_blank\" rel=\"noreferrer noopener\">large language models\u003C\u002Fa> and various \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fgenerative-adversarial-networks-how-can-ai-learn-so-much-while-its-iq-remains-zero\" target=\"_blank\" rel=\"noreferrer noopener\">machine learning methods\u003C\u002Fa> – is able to reach artificial narrow intelligence (ANI) in multiple fields, the first level of intelligence created by humans. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Yet, we have \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.deeplearning.ai\u002Fthe-batch\u002Fartificial-general-intelligence-progress-report\u002F\" target=\"_blank\">not arrived at artificial general intelligence\u003C\u002Fa> (AGI)\u003C\u002Fstrong>, the second level of intelligence when a machine is capable of abstracting concepts from limited experience and transferring knowledge between domains. The third and most fearful domain, superintelligence, when AI evolves into a stand-alone consciousness, is nowhere close.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Yet, ANI and its two main streams, natural language processing, and computer vision, are developing at an incredible speed. The latter is crucial for diagnostics in healthcare as it is based on pattern recognition. Countless algorithms are currently trained to categorize various patterns seen in medical images and thus help doctors diagnose conditions. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The limitations of such studies are present in at least three areas. At first, used medical evidence tends to originate from highly developed regions containing their specificity or the framework for conceptualizing the algorithm itself incorporates the subjective assumptions of the working team. Secondly, the forecasting and predictive abilities of smart algorithms are anchored in previous cases – however, they might be useless in new cases of drug side effects or treatment resistance.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Finally, the majority of the already conducted AI research has been done on training data sets collected from various medical facilities and after the algorithm analyses the images, doctors are provided with the same dataset – usually without reproducing the clinical conditions. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>That does not decrease the theoretical value of the study – but its practical implementation. Life is no training data set. Thousands of patients come and go to a hospital with thousands of symptoms and describe similar or the same conditions very differently. Thus, the results of AI studies conducted on training data sets might not be representative of what would happen in real-life situations. Common interpretations often leave out these limitations focusing on presenting these studies as ultimate revelations.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Keeping all these constraints in mind, here are the top AI algorithms that we recently found in healthcare.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">1) The algorithm spotting DNA mutations in tumors\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>One of the reasons why it’s so incredibly difficult to treat cancer is that malignant tumors tend to mutate, grow, evolve and change. In the last years, scientists discovered that not only cancer itself transforms but so does its DNA. As sequencing costs significantly dropped, the genetic analysis of tumors became possible, and recently, \u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fthe-human-os\u002Fbiomedical\u002Fdiagnostics\u002Fmachine-learning-tool-can-spot-mutations-in-tumors\" target=\"_blank\" rel=\"noreferrer noopener\">human experts with the support of computational tools started to analyze the data\u003C\u002Fa> to figure out what kinds of genetic changes, or mutations, occur.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":22989,\"width\":\"800px\",\"height\":\"450px\",\"sizeSlug\":\"full\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-full is-resized\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FFuture-of-pathology.png\" alt=\"creativity in healthcare, TMF\" class=\"wp-image-22989\" style=\"width:800px;height:450px\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>For making such existing tools more precise, Personal Genome Diagnostics in Baltimore developed a new method involving machine learning that automates the tumor DNA diagnostic process and improves the accuracy of identifying mutations in cancerous tissues. Bearing that result in mind, the doctor can choose the specific targeted treatment for the patient.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">2) Can AI score better in classifying heart images than humans?\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Echocardiograms produce sound waves to paint the heart’s picture – from which cardiologists can identify whether the patient has any heart disease. It’s a standard test to check for problems with valves or chambers of our central organ, for congenital heart defect or whether shortness of breath or chest pain is in connection with the heart. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>A fascinating development in this field \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41586-023-05947-3\" target=\"_blank\">came from the researchers of Cedars Sinai’s Smidt Heart Institute\u003C\u002Fa> and Division of Artificial Intelligence in Medicine. They reported that artificial intelligence (AI) proved more successful in assessing and diagnosing cardiac function when compared to echocardiogram assessments made by sonographers. In this first randomized, blinded trial cardiologists evaluated 3,495 transthoracic echocardiogram studies, comparing initial assessment by artificial intelligence or by a sonographer. One of the major findings was that cardiologists more frequently agreed with the AI initial assessment, such that they corrected only 16.8% of the initial assessments made by AI and simultaneously corrected 27.2% of the initial assessments made by the sonographers.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Of course, this was not the first initiative to use AI in cardiology. Earlier Rima Arnaut, an assistant professor and practising cardiologist at UC San Francisco and her colleagues used \u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fthe-human-os\u002Fbiomedical\u002Fdiagnostics\u002Fai-cardiologist-aces-its-first-medical-exam\">deep learning to train an AI system that can classify echocardiograms\u003C\u002Fa> according to the type of view shown. When both the AI and expert cardiologists were asked to sort the images, the algorithm achieved an accuracy of 92 percent. The humans got only 79 percent correct. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">3) Heart attack predicting algorithms\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Smart algorithms do not only outperform doctors when it comes to classifying but also in predicting outcomes based on various factors. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fthe-human-os\u002Fbiomedical\u002Fdiagnostics\u002Fai-predicts-heart-attacks-more-accurately-than-standard-doctor-method\" target=\"_blank\">Researchers at the University of Nottingham in the UK created a system\u003C\u002Fa> that scanned patients’ routine medical data and predicted which of them would have heart attacks or strokes within 10 years. When compared to the standard method of prediction based on well-established risk factors such as high blood pressure, cholesterol, age, smoking, and diabetes, the AI system correctly predicted the fates of 355 more patients.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>There are many promising initiatives in this field, some aim \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.news-medical.net\u002Fnews\u002F20220517\u002FUsing-AI-to-predict-heart-attacks.aspx\" target=\"_blank\">to predict heart attacks\u003C\u002Fa> years \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fedition.cnn.com\u002F2022\u002F11\u002F29\u002Fhealth\u002Fheart-attack-stroke-x-ray\u002Findex.html\" target=\"_blank\">before they actually occurred\u003C\u002Fa>, another distinguishes \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.cedars-sinai.org\u002Fnewsroom\u002Fpredicting-sudden-cardiac-arrest\u002F\" target=\"_blank\">between treatable and untreatable\u003C\u002Fa> sudden cardiac arrests, while this algorithm helps to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.bhf.org.uk\u002Fwhat-we-do\u002Fnews-from-the-bhf\u002Fnews-archive\u002F2022\u002Faugust\u002Fartificial-intelligence-could-help-narrow-heart-attack-gender-gap\" target=\"_blank\">more accurately detect heart attacks in women\u003C\u002Fa>, whose condition often remains undetected under standard circumstances. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">4) More precise skin cancer diagnoses with AI\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>According to \u003Ca href=\"https:\u002F\u002Fwww.iarc.who.int\u002Fcancer-type\u002Fskin-cancer\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">statistics from the WHO\u003C\u002Fa>, currently, around 1.5 million non-melanoma skin cancers and 325,000 melanoma skin cancers occur each year globally. Digital health technologies, such as\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-2023-skin-checking-apps-landscape-infographic\" target=\"_blank\" rel=\"noreferrer noopener\"> smartphone apps\u003C\u002Fa> like \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Faspiring-dermatology-app-under-the-microscope-the-skinvision-review\" target=\"_blank\">SkinVision\u003C\u002Fa>, telemedical services as well as AI are at the frontlines of fighting the widely prevalent disease.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":34783,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01-768x432.png\" alt=\"Emerging Trend Alert – Skin Checking Algorithms\" class=\"wp-image-34783\"\u002F>\u003Cfigcaption class=\"wp-element-caption\">Skin Checking Algorithms\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Although several research groups developed smart algorithms for diagnosing skin cancer already, the \u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fthe-human-os\u002Fbiomedical\u002Fdiagnostics\u002Fcomputer-diagnoses-skin-cancers\" target=\"_blank\" rel=\"noreferrer noopener\">one created at Stanford University is likely the most robust system\u003C\u002Fa> so far. It was trained on more than 1.28 million images and fine-tuned with a set of nearly 130,000 scans of skin lesions from more than 2000 diseases. That’s the most extensive dataset used for automated skin cancer classification as of yet. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">5) AI systems for the ICU\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Intensive care units are battlegrounds for human lives. As every moment counts, patients are monitored 24\u002F7 with an army of devices. Constantly beeping bedside monitors show blood pressure, heart rate or any other vital signs of the patient, a machine takes care of the function of the lungs as best as possible, and another goes for the heart. However, these instruments are usually not connected, they are isolated units in the concert of ICU care.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">6) AI detecting breast cancer\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Breast cancer is the most commonly occurring cancer in women and the second most common cancer overall. In spite of global awareness-raising and prevention efforts, there were \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.wcrf.org\u002Fdietandcancer\u002Fcancer-trends\u002Fbreast-cancer-statistics\" target=\"_blank\">over 2 million new cases in 2020\u003C\u002Fa>. The statistics also show that almost 700,000 women died from breast cancer in 2020.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":23124,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled-768x433.png\" alt=\"Women and digital health\" class=\"wp-image-23124\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>As in the case of many other cancer types, early detection could be a lifesaver. However, women with dense breasts have a higher risk of undergoing mammogram screenings that miss signs of breast cancer. Researchers at the University of California, San Francisco found that commercial software for automatically classifying breast density and thus detecting breast cancer is just as accurate as human radiologists. Shortly, the algorithm could support doctors with cases when breast density would not allow clear diagnosis.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Algorithms could not only assist radiologists but also pathologists in their fight against breast cancer. The \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F1606.05718\" target=\"_blank\" rel=\"noreferrer noopener\">International Symposium on Biomedical Imaging (ISBI) held a grand challenge to evaluate computational systems\u003C\u002Fa> for the automated detection of metastatic breast cancer. The winning study showed that combining the efforts of the human pathologist and the deep learning system’s predictions, the human error rate decreased by 85 percent when identifying metastatic breast cancer.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>That’s an impressive result, especially bearing in mind that early diagnosis means saving lives when it comes to the lethal disease. Beyond the achievement, it is worth noting that the joint efforts of AI and human doctors indicated a significant improvement in diagnosing, their single results were not even close.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>AI is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.nytimes.com\u002F2023\u002F03\u002F05\u002Ftechnology\u002Fartificial-intelligence-breast-cancer-detection.html\" target=\"_blank\">already used in Hungary\u003C\u002Fa>, where at five hospitals and clinics that perform more than 35,000 screenings a year, AI systems were rolled out starting in 2021 and now help to check for signs of cancer that a radiologist may have overlooked.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">7) Smart algorithm predicting suicide risk\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In the future, you might go to the hospital with a broken arm and leave the facility with a cast and a note with a compulsory psychiatry session due to flagged suicide risk. That’s what some scientists aim for with their AI system developed to catch depressive behaviour early on and help reduce the emergence of severe mental illnesses.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The \u003Ca href=\"http:\u002F\u002Fjournals.sagepub.com\u002Fdoi\u002Fabs\u002F10.1177\u002F2167702617691560?journalCode=cpxa\" target=\"_blank\" rel=\"noreferrer noopener\">machine-learning algorithm\u003C\u002Fa> created at Vanderbilt University Medical Center in Nashville, uses hospital admissions data, including age, gender, zip code, medication, and diagnostic history, to predict the likelihood of any given individual taking their own life. In trials using data \u003Ca href=\"https:\u002F\u002Fqz.com\u002F1367197\u002Fmachines-know-when-someones-about-to-attempt-suicide-how-should-we-use-that-information\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">gathered from more than 5,000 patients who had been admitted to the hospital for either self-harm or suicide attempts\u003C\u002Fa>, the algorithm was 84% accurate at predicting whether someone would attempt suicide the following week, and 80% accurate at predicting whether someone would attempt suicide within the following two years.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">8) AI predicting death risk among inpatients\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Researchers at Stanford University trained an AI system to increase the number of inpatients who receive end-of-life care exactly when needed – meaning the smart algorithm is able to predict when very seriously ill patients are nearing the end of their lives.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The \u003Ca href=\"https:\u002F\u002Fwww.fastcompany.com\u002F90157967\u002Fthis-ai-predicts-death-could-it-improve-end-of-life-care\" target=\"_blank\" rel=\"noreferrer noopener\">algorithm was trained to analyze diagnoses, prescriptions, demographics, and other factors within electronic health records during that 3 to 12 month period before a patient passed away\u003C\u002Fa>. Once trained, the algorithm was able to flag still-living patients in a hospital’s system that might be appropriate candidates for palliative care. When Stanford Hospital’s palliative care team assessed 50 randomly chosen patients that the algorithm had flagged as being at very high risk, the team found that all of them were appropriate to be referred. Beyond being able to accurately predict, the program also left decision-making in the hands of the doctor entirely. That could be a future model for algorithms and physicians working together as a team.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":47983,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01-768x432.png\" alt=\"robot android artificial intelligence AI algorithm human people man woman\" class=\"wp-image-47983\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">9) MedPaLM, the medical large language model\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Large language models undoubtedly have changed this field forever, they are capable of such high-quality assistance that was never seen earlier. Only a few short weeks after the release of ChatGPT, Google\u002FDeepMind announced \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fpharmaphorum.com\u002Fnews\u002Fgoogle-and-deepmind-share-work-on-medical-chatbot-med-palm\u002F\" target=\"_blank\">the release of MedPaLM\u003C\u002Fa>, a large language model \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">specifically designed to answer healthcare-related questions\u003C\u002Fa>, based on their 540-billion parameter PaLM model.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":48673} -->\n\u003Cfigure class=\"wp-block-image\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002FMedpalm2-768x351.jpg\" alt=\"Medpalm google deepmind large languae model\" class=\"wp-image-48673\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>This model was trained on six existing medical Q&A datasets (NedQA, MedMCQA, PubMedQA, LiveQA, MedicationQA, and MMLU), and the developer teams also created their own HealthSearchQA, using questions about medical conditions and the associated symptoms. At the moment MedPaLM can’t be tested by the general public, but you can read the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2212.13138.pdf\" target=\"_blank\">researcher’s paper here\u003C\u002Fa>. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Very recently \u003Ca href=\"https:\u002F\u002Fcloud.google.com\u002Fblog\u002Ftopics\u002Fhealthcare-life-sciences\u002Fsharing-google-med-palm-2-medical-large-language-model\" target=\"_blank\" rel=\"noreferrer noopener\">the latest iteration was also launched\u003C\u002Fa> and Google provided access to a select group of users, but we haven't seen any studies related to the 2.0 version yet. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">10) The sepsis-watching algorithms\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Duke University researchers developed a Sepsis Watch deep learning algorithm that helps assess a patient’s risk for developing sepsis. It automatically alerts the hospital’s rapid response team in case of a high-risk patient and guides them through the first 3 hours of care administration. This is critical in preventing complications. The university has been working on this algorithm for years and implemented the model in clinical work in 2018. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.advisory.com\u002Fdaily-briefing\u002F2022\u002F04\u002F12\u002Fai-hospitals\" target=\"_blank\">According to Mark Sendak\u003C\u002Fa>, a physician and clinical data scientist at Duke who co-led the project, Duke is conducting a final analysis, but he noted that mortality seems to be down.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Hospital chain HCA Healthcare also developed a predictive algorithm called Sepsis Prediction and Optimisation of Therapy. It continuously monitors patient data to identify potentially impending sepsis cases. The algorithm is able to detect sepsis six hours earlier—and more accurately—than clinicians, enabling the health care system to cut sepsis mortality rates across 160 hospitals by nearly 30% – \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.wsj.com\u002Farticles\u002Fhow-hospitals-are-using-ai-to-save-lives-11649610000\" target=\"_blank\">The Wall Street Journal reported\u003C\u002Fa>.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":32755,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_246-01-768x432.png\" alt=\"\" class=\"wp-image-32755\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">We better look at AI as our new colleague\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>There are many more excellent examples of smart algorithms in healthcare, and a lot more will come in the future. But the last one showed the essence of digital health: the best results are achieved by the cooperative work of artificial intelligence and human doctors. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>As artificial intelligence (AI) is set to revolutionise medical practice, it is vital for medical students, young and practising doctors to be well-prepared for the changing landscape. The rapid advancements in AI have brought about a major paradigm shift.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I have already said many times before, AI will not replace doctors, but doctors using AI will replace those who are not keeping up with this revolution. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.thinkific.com\u002Fcourses\u002Fintroduction-to-artificial-intelligence-in-medicine-and-healthcare\" target=\"_blank\">Embracing and integrating AI technologies into medical practice\u003C\u002Fa> will not only benefit patients but also enhance the careers of those who are well-equipped for this new era of medicine.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:html -->\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 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\u003C!-- \u002Fwp:html -->","Top Smart Algorithms In Healthcare","As artificial intelligence tools have been invading more or less every area of healthcare, we made a list to keep track of the top smart algorithms aiming for better diagnostics, more sophisticated patient care or further sighted predictions of diseases. ","top-ai-algorithms-healthcare",0,"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=22987&_wpnonce=faf4ca9c84&status=auto-draft&type=post","post","raw",{"yoast_wpseo_title":91,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":15},"FDA-Approved AI-Based Medical Devices - The Medical Futurist",{"self":93,"collection":99,"about":102,"author":105,"replies":109,"wp:featuredmedia":112,"wp:attachment":115,"wp:term":118,"curies":122},[94],{"href":95,"targetHints":96},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F51091",{"allow":97},[98],"GET",[100],{"href":101},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic",[103],{"href":104},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Finfographic",[106],{"embeddable":107,"href":108},true,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[110],{"embeddable":107,"href":111},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=51091",[113],{"embeddable":107,"href":114},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F51093",[116],{"href":117},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=51091",[119],{"taxonomy":120,"embeddable":107,"href":121},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=51091",[123],{"name":124,"href":125,"templated":107},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[127,209,293,382,465,553],{"id":128,"date":129,"date_gmt":130,"guid":131,"modified":133,"modified_gmt":134,"slug":135,"status":13,"type":14,"link":136,"title":137,"content":139,"excerpt":141,"author":23,"featured_media":143,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":144,"class_list":149,"better_featured_image":151,"acf":180,"yoast_meta":181,"_links":183},61131,"2026-08-31T09:10:43","2026-08-31T07:10:43",{"rendered":132},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=61131","2026-08-31T09:10:44","2026-08-31T07:10:44","how-physicians-will-use-ai-3-layers","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Fhow-physicians-will-use-ai-3-layers\u002F",{"rendered":138},"How Physicians Will Use AI: 3 Layers",{"rendered":140,"protected":20},"\n\u003Cp>Here is how physicians will use 3 layers of AI.\u003C\u002Fp>\n\n\n\n\u003Cp>1️⃣ Generalist AI assistants: The thinking and communication layer.\u003C\u002Fp>\n\n\n\n\u003Cp>2️⃣ Medical AI assistants: The evidence and clinical knowledge layer.\u003C\u002Fp>\n\n\n\n\u003Cp>3️⃣ Embedded workflow AI agents: The invisible productivity layer.\u003C\u002Fp>\n\n\n\n\u003Cp>I think this perspective is especially useful for pharma companies.\u003C\u002Fp>\n\n\n\n\u003Cp>Because if you want to understand the future of medical affairs, education, engagement or field force strategy, you first have to understand how your target physicians will actually use AI.\u003C\u002Fp>\n\n\n\n\u003Cp>And they won’t use “one AI.”\u003C\u002Fp>\n\n\n\n\u003Cp>They will work in a layered ecosystem where AI supports how they think, how they access evidence and how their daily workflows run in the background.\u003C\u002Fp>\n\n\n\n\u003Cp>That changes everything about how we reach, support and collaborate with physicians.\u003C\u002Fp>\n",{"rendered":142,"protected":20},"\u003Cp>Here is how physicians will use 3 layers of AI. 1️⃣ Generalist AI assistants: The thinking and communication layer. 2️⃣ Medical AI assistants: The evidence […]\u003C\u002Fp>\n",61133,[145,146,147,148],1833,1723,2015,4177,[150,14,29,30,31,32],"post-61131",{"id":143,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":152,"post":128,"source_url":179},{"width":153,"height":154,"file":155,"filesize":156,"sizes":157,"image_meta":177},1500,1874,"2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s.png",1850974,{"medium":158,"large":162,"thumbnail":167,"medium_large":171,"1536x1536":172},{"file":159,"width":43,"height":44,"mime-type":45,"filesize":160,"source_url":161},"TMF-How-Physicians-will-use-AI-s-370x208.png",46160,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s-370x208.png",{"file":163,"width":50,"height":164,"mime-type":45,"filesize":165,"source_url":166},"TMF-How-Physicians-will-use-AI-s-768x959.png",959,318899,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s-768x959.png",{"file":168,"width":56,"height":56,"mime-type":45,"filesize":169,"source_url":170},"TMF-How-Physicians-will-use-AI-s-150x150.png",18440,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s-150x150.png",{"file":163,"width":50,"height":164,"mime-type":45,"filesize":165,"source_url":166},{"file":173,"width":174,"height":63,"mime-type":45,"filesize":175,"source_url":176},"TMF-How-Physicians-will-use-AI-s-1229x1536.png",1229,741072,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s-1229x1536.png",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":178},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F08\u002FTMF-How-Physicians-will-use-AI-s.png",{"related_article":20},{"yoast_wpseo_title":182,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":136},"How Physicians Will Use AI: 3 Layers - The Medical Futurist",{"self":184,"collection":189,"about":191,"author":193,"replies":195,"wp:featuredmedia":198,"wp:attachment":201,"wp:term":204,"curies":207},[185],{"href":186,"targetHints":187},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F61131",{"allow":188},[98],[190],{"href":101},[192],{"href":104},[194],{"embeddable":107,"href":108},[196],{"embeddable":107,"href":197},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=61131",[199],{"embeddable":107,"href":200},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F61133",[202],{"href":203},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=61131",[205],{"taxonomy":120,"embeddable":107,"href":206},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=61131",[208],{"name":124,"href":125,"templated":107},{"id":210,"date":211,"date_gmt":212,"guid":213,"modified":215,"modified_gmt":216,"slug":217,"status":13,"type":14,"link":218,"title":219,"content":221,"excerpt":223,"author":23,"featured_media":225,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":226,"class_list":229,"better_featured_image":231,"acf":264,"yoast_meta":265,"_links":267},60709,"2026-05-05T09:24:53","2026-05-05T07:24:53",{"rendered":214},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=60709","2026-05-05T09:25:00","2026-05-05T07:25:00","worldwide-ai-statistics","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Fworldwide-ai-statistics\u002F",{"rendered":220},"Worldwide AI Statistics",{"rendered":222,"protected":20},"\n\u003Cp>I looked into how many people use AI and, particularly, large language models worldwide. I merged all the statistics I could find:\u003Cbr>\u003Cbr>1) People who have NEVER used AI: ~6 billion people (≈75%)\u003Cbr>\u003Cbr>2) People who use free LLMs: ~1-1,5 billion people\u003Cbr>\u003Cbr>3) People using health-related LLMs ~100 – 300 million people weekly\u003Cbr>\u003Cbr>4) The tiny white dot: People who can use prompt and context engineering.\u003Cbr>\u003Cbr>The last point is crucial because those represent the skills we all need to exploit the advantages of such available AI models.\u003C\u002Fp>\n",{"rendered":224,"protected":20},"\u003Cp>I looked into how many people use AI and, particularly, large language models worldwide. I merged all the statistics I could find: 1) People who […]\u003C\u002Fp>\n",60711,[145,227,228],2313,1583,[230,14,29,30,31,32],"post-60709",{"id":225,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":232,"post":210,"source_url":263},{"width":69,"height":233,"file":234,"filesize":235,"sizes":236,"image_meta":260,"original_image":262},2560,"2026\u002F05\u002FTMF-AI-usage-3-scaled.png",895397,{"medium":237,"large":241,"thumbnail":246,"medium_large":250,"1536x1536":251,"2048x2048":255},{"file":238,"width":43,"height":44,"mime-type":45,"filesize":239,"source_url":240},"TMF-AI-usage-3-370x208.png",3727,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-370x208.png",{"file":242,"width":50,"height":243,"mime-type":45,"filesize":244,"source_url":245},"TMF-AI-usage-3-768x960.png",960,142799,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-768x960.png",{"file":247,"width":56,"height":56,"mime-type":45,"filesize":248,"source_url":249},"TMF-AI-usage-3-150x150.png",4821,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-150x150.png",{"file":242,"width":50,"height":243,"mime-type":45,"filesize":244,"source_url":245},{"file":252,"width":174,"height":63,"mime-type":45,"filesize":253,"source_url":254},"TMF-AI-usage-3-1229x1536.png",333516,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-1229x1536.png",{"file":256,"width":257,"height":69,"mime-type":45,"filesize":258,"source_url":259},"TMF-AI-usage-3-1638x2048.png",1638,579491,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-1638x2048.png",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":261},[],"TMF-AI-usage-3.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F05\u002FTMF-AI-usage-3-scaled.png",{"related_article":20},{"yoast_wpseo_title":266,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":218},"Worldwide AI Statistics - The Medical Futurist",{"self":268,"collection":273,"about":275,"author":277,"replies":279,"wp:featuredmedia":282,"wp:attachment":285,"wp:term":288,"curies":291},[269],{"href":270,"targetHints":271},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F60709",{"allow":272},[98],[274],{"href":101},[276],{"href":104},[278],{"embeddable":107,"href":108},[280],{"embeddable":107,"href":281},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60709",[283],{"embeddable":107,"href":284},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60711",[286],{"href":287},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60709",[289],{"taxonomy":120,"embeddable":107,"href":290},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60709",[292],{"name":124,"href":125,"templated":107},{"id":294,"date":295,"date_gmt":296,"guid":297,"modified":299,"modified_gmt":300,"slug":301,"status":13,"type":14,"link":302,"title":303,"content":305,"excerpt":307,"author":23,"featured_media":309,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":310,"class_list":313,"better_featured_image":315,"acf":344,"yoast_meta":354,"_links":356},60603,"2026-04-13T11:58:38","2026-04-13T09:58:38",{"rendered":298},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=60603","2026-04-13T11:58:46","2026-04-13T09:58:46","the-current-state-of-over-1450-fda-approved-ai-based-medical-devices","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Fthe-current-state-of-over-1450-fda-approved-ai-based-medical-devices\u002F",{"rendered":304},"The Current State Of Over 1450 FDA-Approved, AI-Based Medical Devices",{"rendered":306,"protected":20},"\n\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\n\n\n\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\n\n\n\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",{"rendered":308,"protected":20},"\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 […]\u003C\u002Fp>\n",60507,[145,311,312,146],4295,1683,[314,14,29,30,31,32],"post-60603",{"id":309,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":316,"post":342,"source_url":343},{"width":317,"height":233,"file":318,"filesize":319,"sizes":320,"image_meta":339,"original_image":341},2327,"2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-scaled.jpg",385601,{"medium":321,"large":326,"thumbnail":330,"medium_large":334,"1536x1536":335},{"file":322,"width":43,"height":44,"mime-type":323,"filesize":324,"source_url":325},"20260324_FDA-Approved-AI-Based-Medical-Devices-small-370x208.jpg","image\u002Fjpeg",16406,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-370x208.jpg",{"file":327,"width":50,"height":51,"mime-type":323,"filesize":328,"source_url":329},"20260324_FDA-Approved-AI-Based-Medical-Devices-small-768x845.jpg",86468,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-768x845.jpg",{"file":331,"width":56,"height":56,"mime-type":323,"filesize":332,"source_url":333},"20260324_FDA-Approved-AI-Based-Medical-Devices-small-150x150.jpg",9421,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-150x150.jpg",{"file":327,"width":50,"height":51,"mime-type":323,"filesize":328,"source_url":329},{"file":336,"width":62,"height":63,"mime-type":323,"filesize":337,"source_url":338},"20260324_FDA-Approved-AI-Based-Medical-Devices-small-1396x1536.jpg",195796,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-1396x1536.jpg",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":340},[],"20260324_FDA-Approved-AI-Based-Medical-Devices-small.jpg",51165,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F07\u002F20260324_FDA-Approved-AI-Based-Medical-Devices-small-scaled.jpg",{"related_article":345},{"ID":342,"post_author":79,"post_date":346,"post_date_gmt":347,"post_content":348,"post_title":304,"post_excerpt":349,"post_status":13,"comment_status":25,"ping_status":25,"post_password":19,"post_name":350,"to_ping":19,"pinged":19,"post_modified":351,"post_modified_gmt":352,"post_content_filtered":19,"post_parent":86,"guid":353,"menu_order":86,"post_type":88,"post_mime_type":19,"comment_count":73,"filter":89},"2026-03-25 10:09:43","2026-03-25 09:09:43","\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":51171,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-1-768x432.png\" alt=\"\" class=\"wp-image-51171\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>From zero to hero\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":51173,\"sizeSlug\":\"full\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-2.png\" alt=\"AI-based medical devices\" class=\"wp-image-51173\"\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\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>The exponential growth we witness now\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":60507,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg 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\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>1995: 2\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>1997: 1\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>1998: 2\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2001: 2\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2002: 1\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2004: 1\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2005: 1\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2006: 1\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2008: 5\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2010: 3\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2011: 3\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2012: 5\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2013: 4\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2014: 6\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2015: 6\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2016: 18\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2017: 27\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2018: 65\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2019: 80\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2020: 114\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2021: 130\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2022: 163\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2023: 226\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2024: 236\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>2025: 350  \u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Which specialties are most affected?\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Here is the full list:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>Radiology 1104\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Cardiovascular 141\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Neurology 67\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Anesthesiology 27\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Gastroenterology-Urology 26\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Hematology 21\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>The FDA submission types\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>the 510(k) is the most popular with 1396 (+201 since last year) approvals so far,\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>leaving De Novo 37 (+1)\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>and pre-market 18 (+2) far behind. \u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":51169,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F06\u002Fimage-768x432.png\" alt=\"\" class=\"wp-image-51169\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\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\u003C!-- \u002Fwp:paragraph -->","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.","the-current-state-of-fda-approved-ai-based-medical-devices","2026-03-27 06:17:13","2026-03-27 05:17:13","https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=51165&_wpnonce=66b92b2f0d&status=auto-draft&type=post",{"yoast_wpseo_title":355,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":302},"The Current State Of Over 1450 FDA-Approved, AI-Based Medical Devices - The Medical Futurist",{"self":357,"collection":362,"about":364,"author":366,"replies":368,"wp:featuredmedia":371,"wp:attachment":374,"wp:term":377,"curies":380},[358],{"href":359,"targetHints":360},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F60603",{"allow":361},[98],[363],{"href":101},[365],{"href":104},[367],{"embeddable":107,"href":108},[369],{"embeddable":107,"href":370},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60603",[372],{"embeddable":107,"href":373},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60507",[375],{"href":376},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60603",[378],{"taxonomy":120,"embeddable":107,"href":379},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60603",[381],{"name":124,"href":125,"templated":107},{"id":383,"date":384,"date_gmt":385,"guid":386,"modified":388,"modified_gmt":389,"slug":390,"status":13,"type":14,"link":391,"title":392,"content":394,"excerpt":396,"author":23,"featured_media":398,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":399,"class_list":402,"better_featured_image":404,"acf":428,"yoast_meta":437,"_links":439},60599,"2026-04-13T11:56:41","2026-04-13T09:56:41",{"rendered":387},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=60599","2026-04-13T11:56:42","2026-04-13T09:56:42","inside-the-worlds-most-comprehensive-longevity-package","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Finside-the-worlds-most-comprehensive-longevity-package\u002F",{"rendered":393},"Inside the World’s Most Comprehensive Longevity Package",{"rendered":395,"protected":20},"\n\u003Cp>When the CEO of MediPredict reached out to offer me their full longevity and health prevention package, I couldn’t say no, even though it wasn’t an easy decision.\u003C\u002Fp>\n\n\n\n\u003Cp>I share the whole experience, what tests I took, what I learnt and what will be different in my health journey from now on.\u003C\u002Fp>\n\n\n\n\u003Cp>I also summarized 10 insights about longevity after this experience.\u003C\u002Fp>\n",{"rendered":397,"protected":20},"\u003Cp>When the CEO of MediPredict reached out to offer me their full longevity and health prevention package, I couldn’t say no, even though it wasn’t […]\u003C\u002Fp>\n",60601,[400,401],1873,1571,[403,14,29,30,31,32],"post-60599",{"id":398,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":405,"post":383,"source_url":427},{"width":406,"height":407,"file":408,"filesize":409,"sizes":410,"image_meta":425},1280,720,"2026\u002F04\u002F1771413987562.jpg",86311,{"medium":411,"large":415,"thumbnail":420,"medium_large":424},{"file":412,"width":43,"height":44,"mime-type":323,"filesize":413,"source_url":414},"1771413987562-370x208.jpg",13275,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002F1771413987562-370x208.jpg",{"file":416,"width":50,"height":417,"mime-type":323,"filesize":418,"source_url":419},"1771413987562-768x432.jpg",432,44468,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002F1771413987562-768x432.jpg",{"file":421,"width":56,"height":56,"mime-type":323,"filesize":422,"source_url":423},"1771413987562-150x150.jpg",4557,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002F1771413987562-150x150.jpg",{"file":416,"width":50,"height":417,"mime-type":323,"filesize":418,"source_url":419},{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":426},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F04\u002F1771413987562.jpg",{"related_article":429},{"ID":430,"post_author":79,"post_date":431,"post_date_gmt":432,"post_content":433,"post_title":393,"post_excerpt":19,"post_status":13,"comment_status":25,"ping_status":25,"post_password":19,"post_name":390,"to_ping":19,"pinged":19,"post_modified":434,"post_modified_gmt":435,"post_content_filtered":19,"post_parent":86,"guid":436,"menu_order":86,"post_type":88,"post_mime_type":19,"comment_count":73,"filter":89},59639,"2025-12-10 13:19:33","2025-12-10 12:19:33","\u003C!-- wp:paragraph -->\n\u003Cp>Since the very dawn of the wearable revolution, I have been using \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcategory\u002Fhealth-sensors-trackers\">apps, sensors and devices\u003C\u002Fa> to live a healthy life. I’ve been tweaking my lifestyle decisions with a lot of data since the early 2010s. From smart sleep alarms, genetic tests and fitness trackers to portable ECGs and continuous blood glucose monitors, I’ve tried everything on the market to see what the patient and the physician from the future would go through while using advanced technologies.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>So when Ernő Duda, the CEO of \u003Ca href=\"https:\u002F\u002Fmedipredict.com\u002F\">MediPredict\u003C\u002Fa> reached out to offer me their full longevity and health prevention package, I couldn’t say no, even though it wasn’t an easy decision. I was grateful for the offer, but as a physician, I also knew that measuring everything doesn’t necessarily lead to better insights. We might find things I shouldn’t know about or things that might bother me mentally from now on, without any clinical implications.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Still, discussing it with my future self at the age of 60, I decided to go for it. I couldn’t pass on the opportunity and I wanted to see what a top-tier longevity package looks and feels like.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Plus, the package is worth over 20.000 EUR, so I simply couldn’t say no.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>What surprised me most was not the data itself, but how this experience reshaped my understanding of longevity, risk, and what it actually means to build a relationship with your future self.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I thought the hardest part would be the tests. It wasn’t. What I didn’t expect was how emotionally demanding, psychologically complex, and philosophically revealing this journey would become. This journey taught me truths about longevity that no device or report had ever shown me before.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:quote -->\n\u003Cblockquote class=\"wp-block-quote\">\u003C!-- wp:paragraph -->\n\u003Cp>Disclaimer: As always, The Medical Futurist is not affiliated with the company, the review is not sponsored, and it reflects my opinion. Companies\u002Fservice providers first read our reviews after publication.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\u003C\u002Fblockquote>\n\u003C!-- \u002Fwp:quote -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What does MediPredict really offer?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Based in Budapest, Medipredict has built a longevity-journey framework rooted in multi-omics diagnostics and comprehensive health screening. The company offers a broad portfolio of services, including full genome sequencing, microbiome metagenomics, metabolomics, extensive laboratory parameters and imaging diagnostics. They aim at capturing a deep snapshot of the body’s molecular, metabolic and anatomical state.\u003Ca href=\"https:\u002F\u002Fmedipredict.com\u002F\"> \u003C\u002Fa>The data are then integrated via algorithms and expert teams to deliver an individualized health profile that goes beyond typical preventive check-ups. They sort of predict the patient’s future health journey.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Once the data are collected and analysed, Medipredict provides a personalised report and health-coaching follow-up: the client is guided through results, understands the implications for lifestyle and risk, and receives recommendations tailored to their own biology and context.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What kinds of tests did I have?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I had an initial discussion with a medical professional to sort through my medical records, previous tests, health issues and results. Then, after weeks of preparation and logistics, I had over 30 tests throughout a 4-week-long period, and then four long consultations about the results. Brace yourself, the list of tests is long:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>Full genome sequencing (with special analyses such as cancer or cardiovascular diseases, based on my family history)\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Blood tests (over 300 markers, from hormones and vitamins to tumour markers and blood glucose tolerance test)\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Microbiome testing\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Abdominal ultrasound\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Body composition analysis (DEXA)\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Coronary CT angiography\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Cranial MR angiography\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Osteodensitometry\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Whole-body MRI\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Ambulatory blood pressure monitoring\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Cardio ECG patch\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Exercise tolerance test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Biological age test from blood\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Ophthalmology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Resting ECG and during exercise\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Sleep test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Diet diary\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Spirometry test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Continuous glucose monitoring\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Semen analysis\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Physical Examinations: Dermatology, ENT, Gastroenterology, Internal Medicine, Neurology, Urology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Gastro- and colonoscopy\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Toxin test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:image {\"id\":59643,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002Fvlcsnap-2025-12-09-11h45m30s529-copy-768x432.jpg\" alt=\"\" class=\"wp-image-59643\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Some obvious ones I didn’t have as I recently had them on my own screening schedule, such as neck\u002Fcarotid ultrasound, or low-dose chest CT.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I had some brutal days with multiple tests but I chose to do it this way instead of doing one or two tests every day for a month. For example, on the first day, they took 25 tubes of blood samples, then I had the blood glucose tolerance test. After a quick breakfast, the next step was a full-body MRI, then a brain MRI at a different location, and finally, a fertility test at a fourth location. I’m not going to lie, these were emotionally and physically demanding days.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In general, the whole month was like this and I did worry a lot about the potential results. It’s something (the FOFO, the fear of finding out) you have to pull through unless you are really used to it.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Regarding the results, due to the national electronic medical record system in Hungary, I kept receiving the results before the company, and I knew more or less what they were going to find before the final consultations.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The \u003Cstrong>final consultations\u003C\u002Fstrong> took place in four sittings, a few weeks after my last test was done. The first one was about the medical findings so I could discuss every clinical conclusion with a physician. The second one was about genomics where a genetic counselor walked me through the variations, mutations and disease risks. The third one was dedicated to nutrition and nutrigenomics. And the last one was the integrated service, where I received complex recommendations about how I can keep on working on my health from now on.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What did they find?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>As the company said, it would take a day or two to list every negative finding\u002Fresult and mention everything that is fine with my health, so I won’t do that either. What I share here is about 10% of all the results. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Full genome sequencing (out of a blood sample)\u003C\u002Fstrong>: Out of the 81 clinically important monogenic variants, they found nothing, good news! But, they found 3 variants that might be pathogenic, meaning those might cause a disease. One is called the DSP gene, which might lead to a rare heart condition; one in the Factor V gene that leads to a higher risk for thrombosis, and one called TNFRSF13B that might lead to an autoimmune condition. Also, I have a high genetic risk for obesity and Coeliac disease. They identified a list of 28 medications I would have adverse side effects for. The list includes antidepressants and cholesterol-lowering medications. Regarding the less clinical, but more lifestyle-related variants, I have a muscle type that is more prone to short bursts rather than long distance running; a risk for acne (I suffered a lot as a teenager), I can smell asparagus in my urine (due to an olfactory receptor mutation) and I have Misophonia, an extreme emotional reaction to certain everyday sounds such as eating or chewing.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Blood tests (25 tubes of blood samples)\u003C\u002Fstrong>: A few markers out of the desired range that were surprising, such as Rheumatoid factor or ds-DNA. I'll have them remeasured after 3 months. Blood markers also confirmed my thrombosis risk due to the Leiden factor mutation.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":59671,\"width\":\"309px\",\"height\":\"auto\",\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large is-resized\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F2-768x1024.jpg\" alt=\"\" class=\"wp-image-59671\" style=\"width:309px;height:auto\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Microbiome testing (fecal sample)\u003C\u002Fstrong>: Alpha diversity was 4,87, which is great and means I have a healthy, diverse microbiome. One kind of bacteria is missing from my microbiome, though, Akkermansia Muciniphila. I got food recommendations on how to boost its level. I also got a lot of other details about many things that don't have a clinical or lifestyle consequence, so I won't share them here.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Body composition analysis and Osteodensitometry\u003C\u002Fstrong> \u003Cstrong>(lying in a machine for 30 minutes)\u003C\u002Fstrong>: My bone density is excellent, but body fat is around 25% which is surprisingly bad. I'll work on it with more running sessions.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Coronary CT angiography (an hour-long procedure with some pain and discomfort)\u003C\u002Fstrong>: There was a really tiny coronary wall irregularity, which was not confirmed as a plaque. I plan to redo the test in 5 years.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Whole-body MRI (an hour-long procedure with loud noises in a closed tube, I counted my breathing for comfort, went to 720)\u003C\u002Fstrong>: They found a small cyst in my kidney, and some signs of degeneration in my spine (but I was told these were still minor, and it seems I take good care of myself).\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Cardio ECG patch + Exercise tolerance test (wore a chest patch for a day and used a bicycle for 15 minutes with high intensity while electrodes were on me)\u003C\u002Fstrong>: Minor issues, nothing had any clinical relevance.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":59673,\"width\":\"509px\",\"height\":\"auto\",\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large is-resized\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002Fecg-768x843.png\" alt=\"\" class=\"wp-image-59673\" style=\"width:509px;height:auto\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Biological age test from blood (a few drops of blood samples)\u003C\u002Fstrong>: It was 36 while my real age is 41, I'm happy about it. However, it has no relevance to lifestyle or medical decisions. Just a fun fact I can tell people at dinner parties.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Diet diary (I wrote it for a week with as many details as possible)\u003C\u002Fstrong>: The nutritional recommendations focused less on restrictive rules and more on data-driven optimisation. The guidance emphasised stabilizing energy intake around ~3,100 kcal per day while reducing overall fat consumption and slightly lowering carbohydrates, with sustained attention to protein quality rather than quantity. Fibre intake and hydration were highlighted as areas to maintain or increase, particularly on training days. On a practical level, the plan favors foods that support microbiome diversity, glycaemic stability and recovery. For example, resistant starches (like green bananas, jasmine rice, potatoes), whole plant foods such as legumes, oats, chickpeas, nuts, and cruciferous vegetables, as well as fermented dairy alternatives and polyphenol-rich beverages including green and black tea. It recommends including omega-3s, vitamin D, creatine and magnesium in my diet. Conversely, the assessment advises limiting deep-fried foods, excessive fat intake (including ketogenic patterns), rye-based breads, rapid or high-volume alcohol intake, large single-dose protein loads, and heavily processed meats.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Oral glucose tolerance test (2 hours, 3 blood tests after taking a drink rich in sugar)\u003C\u002Fstrong>: Only my two-hour insulin level was a bit higher than anticipated, which might indicate a long-term risk for insulin tolerance that also runs in my family.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Dermatology (one-hour-long consultation)\u003C\u002Fstrong>: They checked all my skin lesions, and one was spotted for potential removal. As the chance of it becoming malignant is almost zero in a decade, I decided to keep on watching it instead of getting it removed now.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":59647,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002Fvlcsnap-2025-12-09-11h47m50s213-copy-768x432.jpg\" alt=\"\" class=\"wp-image-59647\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>ENT\u003C\u002Fstrong>: I have to do the \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fshorts\u002FNJOX3Ic1CrY\">Valsalva maneuver\u003C\u002Fa> once a day for my entire life due to an ear observation. Everyone should do it by the way.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Internal Medicine\u003C\u002Fstrong>: My cholesterol level was high, so I started implementing changes in my diet (I have to avoid medications for the same purpose due to my genetic sensitivity to almost all of them). My thrombosis risk is confirmed and I took an injection before a recent long flight. I have to be hydrated properly all the time and avoid immobility for longer periods.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Toxin test (from urine test)\u003C\u002Fstrong>: The level of mercury was higher than usual (but not toxic), which might be due to the amount of seafood I eat as part of the Mediterranean diet. It's impossible to do something properly in longevity.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>A list of fully negative examinations and tests:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>Abdominal ultrasound\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Cranial MR angiography\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Ambulatory blood pressure monitoring\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Ophthalmology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Sleep test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Spirometry test\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Continuous glucose monitoring\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Semen analysis\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Gastro- and colonoscopy, Gastroenterology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Neurology, Urology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:image {\"id\":59649,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002Fvlcsnap-2025-12-09-11h49m29s137-copy-768x432.jpg\" alt=\"\" class=\"wp-image-59649\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What’s next in my health journey?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The results of this longevity workup don’t point toward a single dramatic intervention but rather a set of long-term trajectories that now become clearer.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The \u003Cstrong>pathogenic-leaning variants\u003C\u002Fstrong> in DSP, Factor V, and TNFRSF13B don’t demand medical action today, but they create three lifelong surveillance pathways: periodic cardiac imaging for arrhythmogenic cardiomyopathy risk, proactive thrombosis prevention (hydration, movement, flight precautions), and attention to early signs of autoimmune dysregulation. These aren’t diagnoses but probabilistic signals that transform uncertainty into informed vigilance, so I hope. The same is true for my elevated genetic risk for coeliac disease and obesity: neither manifests clinically, but both give shape to areas where lifestyle choices have disproportionately high leverage.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>A second cluster of next steps arises from \u003Cstrong>borderline or mildly abnormal findings\u003C\u002Fstrong>: rechecking autoimmune markers (RF, ds-DNA) to confirm whether they were transient fluctuations; adjusting diet to improve LDL levels without statins (given pharmacogenomic constraints); lowering body fat percentage through structured endurance training; and monitoring insulin dynamics due to a family-linked tendency toward insulin resistance.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Microbiome and nutrition data\u003C\u002Fstrong> shape a third pathway: supporting Akkermansia species in my microbiome, reducing total fat intake, and following a macronutrient structure with food types and a sample diet they have recommended. I already started doing many of them.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Imaging and functional tests\u003C\u002Fstrong> form the final layer of future tasks: repeating coronary CT in five years to track the tiny wall irregularity; keeping an eye on a benign skin lesion; and maintaining spinal health through targeted mobility and strength training with yoga and manual therapy.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The long list of normal tests is not just “nothing to see here.” I will keep on redoing them with a long-term schedule.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In practical terms, my next steps are not extraordinary: improve nutrition, reduce body fat, continue endurance training, stay hydrated, avoid immobility, follow up on autoimmune markers, respect my thrombosis risk, and use my pharmacogenomic profile to avoid medications that would work poorly or cause harm.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>But the difference is that these actions are now personalised by data across genomics, imaging, blood biomarkers, lifestyle patterns, and the microbiome.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What was the service like, and what would I change in their service?\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In reflecting on my MediPredict longevity journey, there are a few aspects I’d suggest improving.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>First, the inclusion of a \u003Cstrong>psychologist \u003C\u002Fstrong>at the start would be invaluable. Even as a physician and longevity enthusiast, I found the process and waiting for results stressful. This would likely be even more challenging for non-medical participants.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Second, the \u003Cstrong>wearable devices\u003C\u002Fstrong> used for ECG, blood pressure, and sleep analysis were outdated and uncomfortable. Modern, more patient-friendly patches and devices exist that share data seamlessly with both patients and clinicians.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":59675,\"width\":\"466px\",\"height\":\"auto\",\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large is-resized\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F6-768x1024.jpg\" alt=\"\" class=\"wp-image-59675\" style=\"width:466px;height:auto\"\u002F>\u003Cfigcaption class=\"wp-element-caption\">Sleep tracking and Holter blood pressure setting before going to bed.\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Third, a \u003Cstrong>dashboard \u003C\u002Fstrong>or progress bar would be immensely helpful. Knowing where I stood in the entire process and how many tests are left would have reduced uncertainty and made the experience smoother.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Fourth, \u003Cstrong>the lag between receiving raw results and having a meaningful clinical interpretation\u003C\u002Fstrong> took months. For non-physicians, this delay could be even more stressful.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Fifth, \u003Cstrong>some tests felt less clinically useful\u003C\u002Fstrong> for immediate decision-making, like the metabolomics or biological age tests. They’re interesting, but not necessarily actionable.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>And finally, \u003Cstrong>some key areas were missing\u003C\u002Fstrong> from this otherwise comprehensive journey: dentistry and oral health, mental health or cognitive baseline testing.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Final conclusions and learning points about longevity\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>First of all, I’m really grateful to MediPredict for giving me this opportunity of a lifetime. Everyone at the company and every physician they work with has been extremely professional, helpful and kind. One of them even told me that it’s heroic to go through all of these tests and examinations as a patient. I have to agree.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>In summary, I’ve learnt more about longevity and my own journey in it in 6 months than in the previous decades. I try to summarize all these conclusions and learning points below.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>1) Longevity requires a LOT of effort, time, privacy, and money.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Before this journey, I thought FOFO (the fear of finding out) was going to be the biggest challenge. But it turns out that they measure so many things and obtain so many data points, that even statistically it’s impossible not to find something.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The real question I had to ask myself is how far I want to go on this recommended, laid out longevity path. And this is the decision I have to make. Will I take every single suggestion and live my life like Bryan Johnson? Will I ditch those fact-based suggestions to live a bit more comfortably?\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I’ll do both. I’ve received about a hundred (!) recommendations and I think I will build about 70 into my life. On some days, it’s going to be 85, and on some other days, maybe 45. That sounds good enough to me.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>2) Dealing with longevity comes with a LOT of health anxiety.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>It doesn’t matter how experienced you are. I've tested hundreds of genetic services and digital health devices before, and during these months, I was full of stress, waiting for the results.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The results and verdicts kept getting into my medical record system and I had to deal with more and more data and conclusions. However, this is like training a muscle. The more you do it, the better you handle it. By the time of the hundredth medical record, my anxiety started to get better.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Also, some findings are more about future risks that I don’t even see the signs of yet. Still, I have to deal with mitigating those risks and follow a screening schedule to keep it this way.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":59645,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002Fvlcsnap-2025-12-09-11h45m14s605-copy-768x432.jpg\" alt=\"\" class=\"wp-image-59645\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>3) New digital health devices can make the experience much better.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>There are new devices in ECG and blood pressure monitoring, among others, that are much more convenient for patients and might even provide the company with more meaningful data. Wearing a bulky Holter blood pressure monitor elt like being in the 1990s. Digital health is mature enough to provide a range of devices that could be clinically relevant and still allow patients to live their lives to the fullest during examinations.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Also, these are the devices (which we review on this channel all the time) that will help patients manage their longevity journeys with data.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>4) It's better to start this journey while you have no major diseases.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>While lying in the very loud MRI machine in a closed space, I got some time to think and I thought it’s much better being in this unbearable machine for an hour now, compared to being in there trying to find out what causes a certain symptom.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Simply speaking, going through all of these while healthy is much easier than doing the same while trying to find out the cause of a disease. I know it’s a luxury to do so, but if you have the chance, please don’t wait for a symptom to prompt you to enter the healthcare ecosystem.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>We will become members of our medical teams long before a disease arises in our bodies. Imagine the kind of market it will create, though, from the need for healthcare navigators, screening services and additional tests focusing on prevention.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>5) I don't see how its cost would go down significantly in the near future, so it might still be a privilege for the richest.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Decisions about preventive health shouldn’t resemble decisions about buying a car, yet this is where longevity packages inevitably land today. Choosing whether I can afford a gym membership or a routine screening is one thing; weighing the cost of an ultra-comprehensive longevity assessment is an entirely different category. The price of such a programme is comparable to purchasing a vehicle, which automatically restricts access to a very small fraction of society. As long as longevity care sits in the same price bracket as major consumer assets, it will remain a privilege rather than a scalable model for population health.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>However, no matter how many not-so-useful tests were included in the package, if you can afford such a thing, I’d say go for it.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>6) The value of personalization and the burden of noise in data\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The real value of the package lies not only in the detection of pathology, but also in learning where not to worry. For example, many findings established baselines, which reduce future uncertainty. These baselines will be a form of psychological safety for me, as I begin my longevity journey. While it was inconvenient to prepare for a colonoscopy, expecting to have one every 5 years, I counted I would have 12 more of these in my lifetime. Hopefully, preparing for that while healthy every single time. It gives a long-term purpose to the whole thing.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Also, comprehensive longevity screening inevitably produces incidental findings. Simply speaking, a lot of noise. The challenge becomes interpreting which ones matter. That's why a whole team helped interpret the results and I also needed my own instinct and sense to sort through the mess of data.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>To give you an example: I talked to them about an anxiety-related symptom, for which, they checked a genetic package for possible causes of palpitation. They found a pathogenic variant that might never cause a disease, or might be the reason for my symptoms. Every year, I’ll mention it when having a cardiac ultrasound, but this “noise” will always be in my head, potentially causing me some more anxiety, while it might be such a minor finding that otherwise would have never come to the surface.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>7) Lifestyle is still the strongest longevity intervention\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Despite all this high-tech testing, the most impactful actions remain:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>movement\u002Fexercise\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>nutrition\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>sleep\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>stress management\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>social connectedness\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>avoiding harmful exposures\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>98% of the recommendations I have started to build into my lifestyle fall into these categories.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Deep diagnostics refine direction, but lifestyle remains the engine. I make hundreds of decisions every day and I guarantee you not all of them will support my longevity goals. But I'm also sure now more of these are in line with that after doing all these tests.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>8) Having a connection to your future self is crucial.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I see myself boarding a spaceship to Mars at the age of 100 as a tourist, and not on a bed. Maybe an exoskeleton can be around me. It’s important to see yourself and have constant communication with your future selves.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Because so many of your daily decisions are intertemporal decisions, meaning that you do something today and will only enjoy the rewards later. I go to the gym today even though I have many things to do, because my 60-year-old self thanks and hugs me in my head.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Start building that relationship today as it is going to be helping you along the way.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>9) Now I know what longevity is not!\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Longevity is not about achieving immortality. Longevity is not about chasing perfect numbers in your health or about eliminating all the medical risks in your life.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Instead, longevity is a helpful balancing concept. A journey of extending the healthy part of life, grounded in self-understanding, data and personalization.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Pursuing longevity is like learning how to play chess as an adult. You will make a LOT of mistakes along the way, but if you dedicate enough effort, you will gradually get better at it. It’s like a muscle you can build and the sooner you start, the higher chances you have of achieving that.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>10) AI plays a role in that journey!\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>As the results kept appearing in my electronic medical record, I naturally turned to generative AI tools to help me make sense of the volume and complexity of information before my final consultations.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>I didn’t use AI to diagnose or draw conclusions, but rather to structure what I was seeing, translate technical terminology, summarise long reports, and help me prepare more informed questions for the clinical team. It was essentially a way to turn an overwhelming stream of findings into something cognitively manageable.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Even as a physician, navigating dozens of lab values, imaging reports, genomic variants and specialist notes is demanding; using AI as a companion to organise, clarify and contextualise the data made the whole experience less chaotic and helped me arrive at the consultations with clearer expectations and a calmer mind.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>And it did help. For example, when my toxin test came back, the company marked the mercury level in my blood as very high, while ChatGPT proved it with sources how that level is far from being toxic or having any clinical relevance. It explained that because this type of laboratory report recommends chelation or detox protocols for even minimal deviations,  these suggestions are business-driven, not medically indicated.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Final thoughts\u003C\u002Fstrong>\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>In the end, this entire journey aligned with the core principle I’ve been writing and speaking about for years: that the future of our health is not a single path but a landscape of possibilities. So deep diagnostics didn’t show me one inevitable future, instead, they showed me the range of futures I can influence.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>And longevity, as I now understand it firsthand, is about learning to navigate that landscape with better maps, clearer signposts, and a stronger relationship with the person I hope to become.\u003C\u002Fstrong> And that, more than any test result, is what makes the effort worthwhile.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->","2025-12-16 09:40:53","2025-12-16 08:40:53","https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=59639&_wpnonce=52c5b97df6&status=auto-draft&type=post",{"yoast_wpseo_title":438,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":391},"Inside the World’s Most Comprehensive Longevity Package - The Medical Futurist",{"self":440,"collection":445,"about":447,"author":449,"replies":451,"wp:featuredmedia":454,"wp:attachment":457,"wp:term":460,"curies":463},[441],{"href":442,"targetHints":443},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F60599",{"allow":444},[98],[446],{"href":101},[448],{"href":104},[450],{"embeddable":107,"href":108},[452],{"embeddable":107,"href":453},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60599",[455],{"embeddable":107,"href":456},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60601",[458],{"href":459},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60599",[461],{"taxonomy":120,"embeddable":107,"href":462},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60599",[464],{"name":124,"href":125,"templated":107},{"id":466,"date":467,"date_gmt":468,"guid":469,"modified":471,"modified_gmt":472,"slug":473,"status":13,"type":14,"link":474,"title":475,"content":477,"excerpt":479,"author":23,"featured_media":481,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":482,"class_list":484,"better_featured_image":486,"acf":516,"yoast_meta":525,"_links":527},60597,"2026-04-13T11:52:49","2026-04-13T09:52:49",{"rendered":470},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=60597","2026-04-13T11:52:50","2026-04-13T09:52:50","the-medical-futurists-100-digital-health-and-ai-companies-of-2026","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Fthe-medical-futurists-100-digital-health-and-ai-companies-of-2026\u002F",{"rendered":476},"The Medical Futurist’s 100 Digital Health And AI Companies Of 2026",{"rendered":478,"protected":20},"\n\u003Cp>I’m proud to introduce The Medical Futurist’s 100 Digital Health and AI Companies of 2026!\u003C\u002Fp>\n\n\n\n\u003Cp>Just like in previous years, we don’t accept any sponsorship or financial support. We do not have any interest or connection in any of the companies listed in the infographic either.\u003C\u002Fp>\n\n\n\n\u003Cp>Here are also 3 insights about the 23 new additions.\u003C\u002Fp>\n",{"rendered":480,"protected":20},"\u003Cp>I’m proud to introduce The Medical Futurist’s 100 Digital Health and AI Companies of 2026! Just like in previous years, we don’t accept any sponsorship […]\u003C\u002Fp>\n",60231,[483],1613,[485,14,29,30,31,32],"post-60597",{"id":481,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":487,"post":514,"source_url":515},{"width":488,"height":489,"file":490,"filesize":491,"sizes":492,"image_meta":512},1800,1326,"2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small.png",1921687,{"medium":493,"large":497,"thumbnail":502,"medium_large":506,"1536x1536":507},{"file":494,"width":43,"height":44,"mime-type":45,"filesize":495,"source_url":496},"The-Medical-Futurist_The-Top-100-Health-Company-small-370x208.png",70542,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small-370x208.png",{"file":498,"width":50,"height":499,"mime-type":45,"filesize":500,"source_url":501},"The-Medical-Futurist_The-Top-100-Health-Company-small-768x566.png",566,273474,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small-768x566.png",{"file":503,"width":56,"height":56,"mime-type":45,"filesize":504,"source_url":505},"The-Medical-Futurist_The-Top-100-Health-Company-small-150x150.png",26444,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small-150x150.png",{"file":498,"width":50,"height":499,"mime-type":45,"filesize":500,"source_url":501},{"file":508,"width":63,"height":509,"mime-type":45,"filesize":510,"source_url":511},"The-Medical-Futurist_The-Top-100-Health-Company-small-1536x1132.png",1132,838755,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small-1536x1132.png",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":513},[],60229,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small.png",{"related_article":517},{"ID":514,"post_author":79,"post_date":518,"post_date_gmt":519,"post_content":520,"post_title":521,"post_excerpt":19,"post_status":13,"comment_status":25,"ping_status":25,"post_password":19,"post_name":473,"to_ping":19,"pinged":19,"post_modified":522,"post_modified_gmt":523,"post_content_filtered":19,"post_parent":86,"guid":524,"menu_order":86,"post_type":88,"post_mime_type":19,"comment_count":73,"filter":89},"2026-01-27 13:41:51","2026-01-27 12:41:51","\u003C!-- wp:paragraph -->\n\u003Cp>I'm proud to introduce The Medical Futurist’s 100 Digital Health and AI Companies of 2026! We have been releasing this list every year since 2017 as a way to highlight companies to watch this year.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The reason to publish this list is simple: the digital health and AI fields are saturated with hype, and distinguishing the promising players from the noise is a challenge. The annual list is our way of cutting through the clamor to spotlight those we believe are genuinely making strides in this space.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:quote -->\n\u003Cblockquote class=\"wp-block-quote\">\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Disclosure\u003C\u002Fstrong>: Just like in previous years, we don’t accept any sponsorship or financial support. We do not have any interest or connection in any of the companies listed in the infographic either.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\u003C\u002Fblockquote>\n\u003C!-- \u002Fwp:quote -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">And how do I select them? \u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Through a lot of work. Throughout the year, I interview dozens of companies, I test and review devices and services. Plus, my analyses are based on discussions I have with actors across the digital health and AI landscape. From startups through government authorities to prominent innovators, I look for key values:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list -->\n\u003Cul class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>A mindset for innovation\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Truly disruptive technology\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Viable business model\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Clear dedication to digital health or healthcare AI\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Active and transparent communication about their products\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\n\n\u003C!-- wp:list-item -->\n\u003Cli>Peer-reviewed studies about their technology are optional, but represent a bonus\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Ful>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Companies are assigned to primary and secondary categories, such as AI, virtual reality, or health management.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">What has changed from 2025 to 2026?\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>The digital health and AI landscapes are always evolving, companies come and go, therefore there have been some changes:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Got excluded\u003C\u002Fstrong>: A total of 23 companies from last year’s list are no longer present. The reasons vary: some have ceased operations or went bankcrupt, others have faded from the public eye, a few have pivoted to new directions or merged with other companies. While many of them still provide value, I simply found others that were more present and dynamic on the market. \u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Here they are: 23andme, 3x4 Genetics, Acurable, BeatO, Bloomlife, Dante Labs, etectRX, Eyeque, Heart Sentinel, HeraMed, Hocoma, iDoc24, Imaware, Medwand, Microsoft Hololens, Nuance Communications, Oncompass Medicine, PilloVR, ResApp, SayHeart, Sensely, Urbandroid, and Woebot.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Cstrong>Changed name\u003C\u002Fstrong>: Three companies have changed names. Arterys is called Tempus Radiology, Augmedix is Commure and Propeller Health is ResMed now.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:image {\"id\":60231,\"sizeSlug\":\"large\",\"linkDestination\":\"none\"} -->\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small-768x566.png\" alt=\"\" class=\"wp-image-60231\"\u002F>\u003C\u002Ffigure>\n\u003C!-- \u002Fwp:image -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F01\u002FThe-Medical-Futurist_The-Top-100-Health-Company-small.png\">A high-resolution version is available here\u003C\u002Fa>.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">The new additions\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Here is the list of the newcomers: RingConn, RedDrop, YourBio, FusionVital, MediPredict, Whoop, Sidekick Health, Suki AI, Viz.ai, Qure.ai, Caresyntax, Moon Surgical, Turbine, Owkin, DeepScribe, Levels, BioIntelliSense, Kohler Health, Hyfe, Bioliberty, fundamental XR, Belong.life, and Eli.health.\u003Cbr>\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:heading -->\n\u003Ch2 class=\"wp-block-heading\">Some insights about the 23 new additions.\u003C\u002Fh2>\n\u003C!-- \u002Fwp:heading -->\n\n\u003C!-- wp:list {\"ordered\":true} -->\n\u003Col class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>\u003Cstrong>Health management is the center of gravity\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Fol>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Look at how many of the new additions converge on health management, even when they come from different angles: RingConn, FusionVital, MediPredict, Whoop, Levels, BioIntelliSense, Kohler Health, Hyfe, Belong.life, and Eli.health.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Health management has become the default destination. Devices, AI, lab testing, and platforms are converging toward continuous health oversight. That’s a structural change.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list {\"ordered\":true,\"start\":2} -->\n\u003Col start=\"2\" class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>\u003Cstrong>Lab testing is moving closer to people, not hospitals\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Fol>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>RedDrop, YourBio, and Eli.health stand out. All three focus on making lab testing easier, more frequent, and more accessible. It's all about decentralized sampling. The lab is no longer a place, but it’s becoming a service.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:list {\"ordered\":true,\"start\":3} -->\n\u003Col start=\"3\" class=\"wp-block-list\">\u003C!-- wp:list-item -->\n\u003Cli>\u003Cstrong>AI companies are clustering around specific clinical friction points\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C!-- \u002Fwp:list-item -->\u003C\u002Fol>\n\u003C!-- \u002Fwp:list -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Problem-specific AI arises! AI for diagnosis, documentation, surgery, clinical trials or drug discovery. Just look at some of the newcomers:\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>Viz.ai → diagnostics and workflow acceleration\u003Cbr>Qure.ai → imaging diagnostics at scale\u003Cbr>DeepScribe, Suki AI → documentation and cognitive load\u003Cbr>Caresyntax → surgical intelligence\u003Cbr>Turbine, Owkin → drug discovery\u003Cbr>Belong.life → patient-facing AI support\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->\n\n\u003C!-- wp:paragraph -->\n\u003Cp>As usual, I'll keep an eye on all of them and also keep watching the space for you. You just have to follow and subscribe to get all the insights.\u003C\u002Fp>\n\u003C!-- \u002Fwp:paragraph -->","The Medical Futurist's 100 Digital Health And AI Companies Of 2026","2026-01-27 13:41:54","2026-01-27 12:41:54","https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60229&_wpnonce=db1e6de787&status=auto-draft&type=post",{"yoast_wpseo_title":526,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":474},"The Medical Futurist’s 100 Digital Health And AI Companies Of 2026 - The Medical Futurist",{"self":528,"collection":533,"about":535,"author":537,"replies":539,"wp:featuredmedia":542,"wp:attachment":545,"wp:term":548,"curies":551},[529],{"href":530,"targetHints":531},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F60597",{"allow":532},[98],[534],{"href":101},[536],{"href":104},[538],{"embeddable":107,"href":108},[540],{"embeddable":107,"href":541},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60597",[543],{"embeddable":107,"href":544},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60231",[546],{"href":547},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60597",[549],{"taxonomy":120,"embeddable":107,"href":550},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60597",[552],{"name":124,"href":125,"templated":107},{"id":554,"date":555,"date_gmt":556,"guid":557,"modified":559,"modified_gmt":560,"slug":561,"status":13,"type":14,"link":562,"title":563,"content":565,"excerpt":567,"author":23,"featured_media":569,"comment_status":25,"ping_status":25,"template":19,"yst_prominent_words":570,"class_list":571,"better_featured_image":573,"acf":602,"yoast_meta":603,"_links":605},59747,"2025-12-15T14:11:52","2025-12-15T13:11:52",{"rendered":558},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=infographic&p=59747","2025-12-15T15:31:18","2025-12-15T14:31:18","number-of-medical-consultations","https:\u002F\u002Fapi.medicalfuturist.com\u002Finfographics\u002Fnumber-of-medical-consultations\u002F",{"rendered":564},"Number of Medical Consultations",{"rendered":566,"protected":20},"\n\u003Cp>When being able to meet a physician with even minor health issues becomes our everyday reality due to worldwide and still increasing doctor shortages, I think patients in those countries will suffer the most, who are used to having the most consultations a year.\u003C\u002Fp>\n\n\n\n\u003Cp>Here they are based on recent OECD data.\u003C\u002Fp>\n\n\n\n\u003Cp>The blue line represents in-person, while the white bar stands for remote consultations in a given year (2023).\u003C\u002Fp>\n\n\n\n\u003Cp>At the same time, those physicians who have the largest number of consultations a year might benefit the most from this transformation. They are on the right side.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003C\u002Fp>\n",{"rendered":568,"protected":20},"\u003Cp>When being able to meet a physician with even minor health issues becomes our everyday reality due to worldwide and still increasing doctor shortages, I […]\u003C\u002Fp>\n",59749,[],[572,14,29,30,31,32],"post-59747",{"id":569,"alt_text":19,"caption":19,"description":19,"media_type":34,"media_details":574,"post":554,"source_url":601},{"width":575,"height":576,"file":577,"filesize":578,"sizes":579,"image_meta":599},1600,895,"2025\u002F12\u002F31_Doctor-consutlations.png",904091,{"medium":580,"large":584,"thumbnail":589,"medium_large":593,"1536x1536":594},{"file":581,"width":43,"height":44,"mime-type":45,"filesize":582,"source_url":583},"31_Doctor-consutlations-370x208.png",43797,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F31_Doctor-consutlations-370x208.png",{"file":585,"width":50,"height":586,"mime-type":45,"filesize":587,"source_url":588},"31_Doctor-consutlations-768x430.png",430,113836,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F31_Doctor-consutlations-768x430.png",{"file":590,"width":56,"height":56,"mime-type":45,"filesize":591,"source_url":592},"31_Doctor-consutlations-150x150.png",8379,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F31_Doctor-consutlations-150x150.png",{"file":585,"width":50,"height":586,"mime-type":45,"filesize":587,"source_url":588},{"file":595,"width":63,"height":596,"mime-type":45,"filesize":597,"source_url":598},"31_Doctor-consutlations-1536x859.png",859,325279,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F31_Doctor-consutlations-1536x859.png",{"aperture":73,"credit":19,"camera":19,"caption":19,"created_timestamp":73,"copyright":19,"focal_length":73,"iso":73,"shutter_speed":73,"title":19,"orientation":73,"keywords":600},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F12\u002F31_Doctor-consutlations.png",{"related_article":20},{"yoast_wpseo_title":604,"yoast_wpseo_metadesc":19,"yoast_wpseo_canonical":562},"Number of Medical Consultations - The Medical Futurist",{"self":606,"collection":611,"about":613,"author":615,"replies":617,"wp:featuredmedia":620,"wp:attachment":623,"wp:term":626,"curies":629},[607],{"href":608,"targetHints":609},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Finfographic\u002F59747",{"allow":610},[98],[612],{"href":101},[614],{"href":104},[616],{"embeddable":107,"href":108},[618],{"embeddable":107,"href":619},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=59747",[621],{"embeddable":107,"href":622},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F59749",[624],{"href":625},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=59747",[627],{"taxonomy":120,"embeddable":107,"href":628},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=59747",[630],{"name":124,"href":125,"templated":107},1788949325636]