[{"data":1,"prerenderedAt":415},["ShallowReactive",2],{"slug-the-12-most-overhyped-technologies-in-healthcare":3},{"post":4,"relatedPosts":182,"relatedBooks":323},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":6,"modified_gmt":7,"slug":10,"status":11,"type":12,"link":13,"title":14,"content":16,"excerpt":19,"author":21,"featured_media":22,"comment_status":23,"ping_status":23,"sticky":24,"template":25,"format":26,"meta":27,"categories":28,"tags":30,"project_category":38,"contact_email_category":41,"yst_prominent_words":42,"class_list":55,"better_featured_image":72,"acf":111,"yoast_meta":126,"_links":129},13949,"2025-09-15T10:09:37","2025-09-15T08:09:37",{"rendered":9},"http:\u002F\u002Fmedicalfuturist.com\u002F?p=13949","the-12-most-overhyped-technologies-in-healthcare","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-12-most-overhyped-technologies-in-healthcare",{"rendered":15},"The Most Overhyped Technologies in Healthcare",{"rendered":17,"protected":18},"\n\u003Cp>The hype about technological development in healthcare should not blind us in terms of the probabilities and possibilities of today’s healthcare and the future of medicine. To remain objective and conscious but still optimistic, let’s look at the most overhyped technologies and keep in mind the realistic development opportunities in healing.\u003C\u002Fp>\n\n\n\n\u003Cp>You know the saying: the pessimist says the glass is half empty, the optimist says it is half full, and, well, the cynic asks who drank the other half? I’m truly an optimist – especially when it comes to the future of medicine and healthcare, but we need to ask the uncomfortable questions as well.\u003C\u002Fp>\n\n\n\n\u003Cp>Thus, my optimism is rooted in facts and objective judgment about the latest trends in healthcare, keeping both feet on the ground. Sensationalist media tends to overhype outstanding medical findings, creative healthcare solutions, and ephemeral experiments for the 15-minute spotlight, which does not help them become viable and sustainable in any way.\u003C\u002Fp>\n\n\n\n\u003Cp>Look at the \u003Ca rel=\"noopener\" href=\"http:\u002F\u002Fwww.vanityfair.com\u002Fnews\u002F2016\u002F09\u002Felizabeth-holmes-theranos-exclusive\" target=\"_blank\">story of Theranos\u003C\u002Fa> and its ill-famed founder, Elizabeth Holmes. After a decade of blind expectations\u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.wsj.com\u002Farticles\u002Ftheranos-has-struggled-with-blood-tests-1444881901\" target=\"_blank\">, The Wall Street Journal has raised serious concerns\u003C\u002Fa> about Theranos’ one-drop blood tests, and we all know now \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theguardian.com\u002Fus-news\u002F2023\u002Fjul\u002F10\u002Felizabeth-holmes-11-year-prison-sentence-shortened-by-two-years\" target=\"_blank\">how it ended\u003C\u002Fa>. Look at \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theguardian.com\u002Fscience\u002Fneurophilosophy\u002F2014\u002Fjun\u002F03\u002Foptogenetic-memory-switch\" target=\"_blank\">Optogenetics\u003C\u002Fa>! The technology using light to control cell behavior in living tissues still remains a promise for the far future. Look at the \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.bbc.com\u002Fnews\u002Fhealth-23348661\" target=\"_blank\">iKnife\u003C\u002Fa> which can detect cancerous tissue during operations! It almost vanished completely.\u003C\u002Fp>\n\n\n\n\u003Cp>If something sounds too good to be true in medicine, extreme caution and clear evidence are required before spreading the word about it, since giving false hope is dangerous.\u003C\u002Fp>\n\n\n\n\u003Cp>Thus, we need to take a moment, set aside the excitement and optimism, and examine disruptive medical innovations in depth and approach them through evidence-based rationality. Overhyping any of them might result in crashing the process of development or creating an investment bubble. By presenting the downsides, we might avoid this scenario and hopefully, they will turn out to be an amazing success.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">1) 3D printed drugs\u003C\u002Fh2>\n\n\n\n\u003Cp>On an utterly boring Wednesday afternoon, you go to the pharmacy on the corner of the street at your wife’s request. You only tell her name to the pharmacist and the next moment her personalised pills are printed out. They are the capsules she requested, in customized dosage, as the doctor prescribed, and tailored to her molecular background. Sounds amazing, right? Unfortunately, we are not there yet…\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"543\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002F3d_printed_drugs_poster-768x543.png\" alt=\"\" class=\"wp-image-28941\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002F3d_printed_drugs_poster-768x543.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002F3d_printed_drugs_poster-1536x1087.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002F3d_printed_drugs_poster.png 1527w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The first 3D-printed drug, Spritam, which dissolves quickly and is used in epilepsy, was approved by the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-the-fda-and-drug-regulations-2\u002F\" target=\"_blank\">US FDA in 2015\u003C\u002Fa>. I also contemplated that small companies may come up with other solutions for creating drugs that can be metabolized faster and reach the market more easily because of this manufacturing method. And I thought whole pharma supply chains would have to be redesigned within years, perhaps even months.\u003C\u002Fp>\n\n\n\n\u003Cp>However, I might have been too optimistic. Right now, the production is slow. Pharma companies are reluctant to adapt to such a new technology which changes how they have been producing drugs for decades. We’ve seen \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002F3dprintingindustry.com\u002Fnews\u002Fartificial-intelligence-group-uses-new-strategy-to-develop-3d-printed-pills-222379\u002F\" target=\"_blank\">some improvements\u003C\u002Fa> in the past decade, but \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002F3dprinting.com\u002Fnews\u002Ffirst-3d-printed-pediatric-medicine-trials-to-begin-in-europe\u002F\" target=\"_blank\">progress\u003C\u002Fa> is slow, and we still only have very few approved drugs on the market.  \u003C\u002Fp>\n\n\n\n\u003Cp>\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">2) \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fgoogles-amazing-digital-contact-lens-can-transform-diabetes-care\u002F\" target=\"_blank\">Digital contact lens (for diabetes or else)\u003C\u002Fa>\u003C\u002Fh2>\n\n\n\n\u003Cp>Google \u003Ca href=\"http:\u002F\u002Fpatentbolt.com\u002F2014\u002F03\u002Fgoogle-takes-their-google-glass-vision-to-smart-contact-lenses.html\" target=\"_blank\" rel=\"noreferrer noopener\">submitted a patent\u003C\u002Fa> to the US Patent & Trademark Office in 2014 that described a digital, multi-sensor contact lens that can also detect blinking, with benefits like turning the page of an e-book with a “blink of an eye”. Later, \u003Ca href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FGoogle_Contact_Lens\" target=\"_blank\" rel=\"noreferrer noopener\">more details\u003C\u002Fa> about the idea emerged, revealing a much more transformative use for the contact lens – measuring blood glucose from tears.\u003C\u002Fp>\n\n\n\n\u003Cp>In 2014, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.washingtonpost.com\u002Fnational\u002Fhealth-science\u002Fgoogle-develops-contact-lens-glucose-monitor\u002F2014\u002F01\u002F16\u002Fe309c822-7f0a-11e3-97d3-b9925ce2c57b_story.html\" target=\"_blank\">Google said\u003C\u002Fa> that according to their most optimistic calculations, the digital contact lens could be released within five years, and trials might start even earlier. However, the project \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theverge.com\u002F2018\u002F11\u002F16\u002F18099193\u002Fverily-novartis-glucose-contact-lens-science-health\" target=\"_blank\">was eventually terminated in 2018\u003C\u002Fa>. And Google was not the only company burning their hands with the smart contact lenses idea. Mojo Vision had the idea to build a micro-LED display into the lenses with a range of sensors to enhance vision but decided “\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.axios.com\u002F2023\u002F01\u002F06\u002Fsmart-contact-lens-startup-mojo-vision-layoffs\" target=\"_blank\">to shift focus\u003C\u002Fa>” and call the project off.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">3) Telemedicine kiosks\u003C\u002Fh2>\n\n\n\n\u003Cp>The idea behind the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fvsee.com\u002Fblog\u002Fthree-reasons-why-healthspot-failed\u002F\" target=\"_blank\">Healthspot telemedicine kiosks\u003C\u002Fa> was to provide convenient, quality care at popular locations such as retail spaces or offices. It was a true integration of telehealth and personal care. Patients connected with providers face-to-face via video screen, and received individualised care right in their neighborhood.\u003C\u002Fp>\n\n\n\n\u003Cp>While at first, it seemed like a revolutionary development, the company went bankrupt. And the reason why? The working model of Healthspot did not provide the real on-demand health service experience it promised, it was too expensive, its target market was too small and the kiosk itself was too big in the era of smartphones being able to play HD-quality videos.\u003C\u002Fp>\n\n\n\n\u003Cp>The kiosk idea didn’t retire with Healthspot: a startup in India has \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.kioskmarketplace.com\u002Fnews\u002Findia-startup-launches-digital-health-check-kiosk\u002F\" target=\"_blank\">just introduced a digital health kiosk\u003C\u002Fa> to provide basic diagnostics like blood pressure, blood sugar and heart conditions in multiple languages. Many people have pocket-sized devices at home that can do the same.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">4) Organs-on-chips\u003C\u002Fh2>\n\n\n\n\u003Cp>Switching from long and extremely expensive clinical trials to tiny microchips that can be used as models of human cells, organs or whole physiological systems provides clear advantages. Drugs or components could be tested on these without limitations, making clinical trials faster and even more accurate (in each case, the conditions and circumstances would be the same). The \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwyss.harvard.edu\u002Fviewpage\u002F461\u002F\" target=\"_blank\">Organs-on-Chips technology\u003C\u002Fa> is able to use stem cells to mimic organs of the body with a series of devices. Many experts believe that this technology could \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.meddeviceonline.com\u002Fdoc\u002Fhuman-organ-mimicking-chip-could-revolutionize-clinical-trials-0001\" target=\"_blank\">revolutionize clinical trials\u003C\u002Fa> and replace animal testing completely. It could also \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftechnologies-that-will-shape-the-future-of-cancer-care\u002F\" target=\"_blank\">improve cancer care\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>Although the experiments are promising, these are still far from a real and total-body simulation of human physiology, and even the pioneer companies \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fseekingalpha.com\u002Farticle\u002F4431909-organovo-new-strategy-targetting-internal-pipeline-development-offers-upside\" target=\"_blank\">have changed focus\u003C\u002Fa>. Not to mention that if organs could be mimicked, connecting the models to each other is more complicated than we would think.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">5) Augmented reality and mixed reality\u003C\u002Fh2>\n\n\n\n\u003Cp>The fact that Pokémon Go conquered the world in a few short weeks several years ago proves that augmented reality has great potential. And although medical AR is a new area of healthcare, there are \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.timesofisrael.com\u002Fin-global-first-shaare-zedek-spine-surgeon-combines-augmented-reality-with-robotics\u002F\" target=\"_blank\">already brilliant ideas about its usage\u003C\u002Fa>. In the future, medical students might study anatomy on virtual dissection tables and not on human cadavers. What we used to learn from huge textbooks will be transformed into virtual 3D solutions and models using augmented reality. During operations, surgeons can see through anatomical structures such as blood vessels in the liver without opening organs, therefore they can perform more precise excisions.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F09\u002Ftmf_article_386-768x432.png\" alt=\"\" class=\"wp-image-52741\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F09\u002Ftmf_article_386-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F09\u002Ftmf_article_386-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F09\u002Ftmf_article_386-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F09\u002Ftmf_article_386.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>There are already various companies offering AR solutions. However, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.microsoft.com\u002Fmicrosoft-hololens\u002Fen-us\" target=\"_blank\">Hololens\u003C\u002Fa> AR goggles are only available for developers and they are very expensive. \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.medgadget.com\u002F2016\u002F07\u002Fhololens-hands-want.html\" target=\"_blank\">According to the experiences of an American surgeon\u003C\u002Fa>, the Hololens has its limitations in terms of user experience as well, which he hopes will be augmented in later versions.\u003C\u002Fp>\n\n\n\n\u003Cp>Granted, we have some already existing good examples of virtual-, augmented- and mixed reality in healthcare, in this article \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002F6-healthcare-examples-of-virtual-augmented-and-mixed-reality\u002F\" target=\"_blank\">we listed six of them\u003C\u002Fa>. However, while we already have \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002F5-ways-medical-vr-is-changing-healthcare\u002F\" target=\"_blank\">quite convincing evidence\u003C\u002Fa> about the medical use of VR, we lack such data for other extended realities. And we also need to mention that all these technologies require heavy investments as all components are super-expensive.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">6) Medical tricorder\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwill-the-medical-tricorder-from-star-trek-become-real\u002F\" target=\"_blank\">When Dr McCoy from Star Trek\u003C\u002Fa> grabbed his tricorder and scanned a patient, the portable, hand–held device immediately listed vital signs, other parameters, and a diagnosis. It was the Swiss Army knife for physicians. The ultimate point-of-care medical device – you can treat the patient wherever he or she is located.\u003C\u002Fp>\n\n\n\n\u003Cp>There are\u002Fwere already various experiments for trying to reach this level of healthcare – such as \u003Ca href=\"https:\u002F\u002Fwww.scanadu.com\u002F\">Scanadu\u003C\u002Fa>, which was an early-stage mobile medical device to empower patients, or \u003Ca href=\"https:\u002F\u002Fwww.viatomtech.com\u002Fcheckme-pro\">Viatom Checkme\u003C\u002Fa>, which not only measures your body temperature but also traces ECG, measures pulse rate and rhythm, oxygen saturation, systolic blood pressure, physical activity and sleep. Many believed that the Qualcomm Tricorder XPrize challenge would lead to the development of a device that can diagnose any disease and give individuals more choices in their own health – but many years have passed and we have no such products widely available.\u003C\u002Fp>\n\n\n\n\u003Cp>In my opinion, even if we see some progress in this area, such new devices will only be able to track a few parameters and conditions. We have many great gadgets to monitor one health parameter or another, but no omnipotent tool that does it all. Right now, the tricorder is far away from reality.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">7) AI\u003C\u002Fh2>\n\n\n\n\u003Cp>Artificial intelligence without doubt will revolutionize medicine and is the most exciting technological advancement we have seen in a while. It has major importance, similar to the seismic changes the Internet has brought. However, it is certainly the most overhyped technology in medicine right now.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"The 3 Scenarios For AI In Healthcare - The Medical Futurist\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FfoivfOVaf4k?start=1&feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>AI will not be the ultimate solution for all medical questions, nor for all pain points of healthcare systems worldwide. And especially, generative AI will not be the omnipotent answer, despite its breathtaking evolution and exciting capabilities.\u003C\u002Fp>\n\n\n\n\u003Cp>Artificial intelligence has amazing potential, but the adaptation curve will be extremely slow, as is the development of the regulatory framework. The whole field needs time to mature, and frankly, as it is as much a cultural shift as a technological breakthrough, we all need more time to gradually adapt to the AI-infused era.  \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">8) Healthcare dashboards and auto-coaches\u003C\u002Fh2>\n\n\n\n\u003Cp>Health data dashboards claim to analyse comprehensive personal health data to provide tailored lifestyle and health advice. In theory, such dashboards promise to synthesize information from various sources — including wearable tech, medical records, and personal habits — to offer insights and guidelines for healthier living.\u003C\u002Fp>\n\n\n\n\u003Cp>However, the reality falls short of the promise. While the idea of a centralized platform capable of delivering personalised health recommendations is captivating, current technology is not yet sophisticated enough to accurately interpret the complex web of factors that influence individual health. The challenge lies not only in gathering vast amounts of data but also in understanding the intricate interplay between genetics, environment, lifestyle, and health.\u003C\u002Fp>\n\n\n\n\u003Cp>Furthermore, these dashboards often lack the clinical validation necessary to ensure their recommendations are medically sound. Without rigorous scientific backing, the advice provided might be generic or, worse, potentially harmful. The enthusiasm surrounding these dashboards has led to a proliferation of discussion and speculation, overshadowing the critical evaluation of their actual capabilities and limitations.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">9) \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F8-exciting-medical-robot-facts\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Humanoid nurse robots\u003C\u002Fa>\u003C\u002Fh2>\n\n\n\n\u003Cp>Humanoid nurse robots aim to support, assist and extend the service health workers are offering. According to experts, in jobs with repetitive and monotonous functions, they might even obtain the capacity to completely replace humans. \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fnewatlas.com\u002Frobear-riken\u002F36219\u002F\" target=\"_blank\">RoBear\u003C\u002Fa>, a bear-shaped robot is able to lift a patient out of bed, \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.aethon.com\u002Ftug\u002Ftughealthcare\u002F\" target=\"_blank\">the TUG robot\u003C\u002Fa> is able to carry around a multitude of racks, carts or bins up to 700 kilograms, and \u003Ca rel=\"noreferrer noopener\" href=\"http:\u002F\u002Fwww.bbc.com\u002Fnews\u002Ftechnology-36528253\" target=\"_blank\">Pepper, the little humanoid “social robot”\u003C\u002Fa> was able to greet and navigate patients through the hospital.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002Fcreepiest-768x432.png\" alt=\"creepy blood drawing robot\" class=\"wp-image-43429\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002Fcreepiest-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002Fcreepiest-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002Fcreepiest-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002Fcreepiest.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Or at least it is the dream. Humanoid nurse robots are far from being an everyday reality. Even the Pepper robot, which was\u003Ca href=\"https:\u002F\u002Fwww.dailymail.co.uk\u002Fsciencetech\u002Farticle-3641468\u002FPepper-robot-finds-job-healthcare-friendly-droid-trialled-two-hospitals-Belgium.html\"> introduced in two Belgian hospitals\u003C\u002Fa>, was \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Ftechnology\u002Fexclusive-softbank-shrinks-robotics-business-stops-pepper-production-sources-2021-06-28\u002F\" target=\"_blank\">reportedly discontinued\u003C\u002Fa> by SoftBank.\u003C\u002Fp>\n\n\n\n\u003Cp>Various robots seem like an obvious answer to ease healthcare workforce shortages: they could assist in a wide range of tasks, even if just as “back office” personnel – to not freak patients out. However, it is not as easy as one might think. As \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMoravec%27s_paradox\" target=\"_blank\">Moravec’s paradox\u003C\u002Fa> explains, contrary to our assumptions, high-level reasoning tasks we find complex, such as playing chess or doing statistical analysis, require relatively little computational power for AI to perform. On the other hand, sensorimotor skills (like walking, getting up from the ground, and image recognition) are more demanding and difficult for AI to replicate.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">10) Virtual reality gloves\u003C\u002Fh2>\n\n\n\n\u003Cp>There are not only goggles but also gloves with which companies experiment to enhance the VR experience. The American company, \u003Ca href=\"https:\u002F\u002Fwww.manus-meta.com\u002Fproducts\u002Fprime-3-haptic-xr\" target=\"_blank\" rel=\"noreferrer noopener\">Manus created gloves\u003C\u002Fa> that give your hands and arms control in virtual reality. In medicine, especially telemedicine such devices would be great assets – physicians could feel and touch patients from a distance, even from continents away while discussing medical issues through telemedical applications.\u003C\u002Fp>\n\n\n\n\u003Cp>Although the concept is brilliant, practice lags behind: it is very difficult to use such gloves, and VR headsets are not always compatible with them. Not to mention the brutal price tags. All in all, the field of tactile feedback seems to have ground to a halt in the past few years.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">11) \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-rise-of-at-home-lab-tests\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">At-home lab tests\u003C\u002Fa>\u003C\u002Fh2>\n\n\n\n\u003Cp>Although the pandemic gave some much-needed momentum to these initiatives, the segment of at-home lab tests remains more of a promise than a reality. Of course, there are existing solutions, and if you google it, the number of possibilities you could buy seems mindblowing. The reality is more sobering: such tests can actually measure only a limited selection of biomarkers with clinical accuracy.\u003C\u002Fp>\n\n\n\n\u003Cp>And even some existing solutions struggle to find a customer base. A few years ago I tried the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftesting-food-gluten-home-nima-sensor-review\u002F\" target=\"_blank\">Nima sensors\u003C\u002Fa> to search for gluten and peanut content in food just for the sake of trying the technology. They worked well and I still believe that provided much-needed services – however, both were discontinued. A laboratory’s worth of diagnostic arsenal in the bathroom sounds good, but we are not there yet.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">12) 3D printed organs\u003C\u002Fh2>\n\n\n\n\u003Cp>Organ transplantation waiting lists are long and barbaric, not to mention the even more hell-like black market specialized for organ traffic. Patients literally need to wait for somebody to die to receive life-saving treatments. Organs created by using the stem cells of the patient would eliminate the dark side of the organ donor systems.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Forgan-design-768x432.png\" alt=\"organ design, tmf, heart, tissue, bioprinting\" class=\"wp-image-41555\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Forgan-design-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Forgan-design-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Forgan-design-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Forgan-design.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Many years have passed since we first saw promising signs, for example when researchers \u003Ca href=\"http:\u002F\u002Fwww.3ders.org\u002Farticles\u002F20160711-roche-researchers-use-organovos-3d-printed-human-liver-tissues-to-assess-drug-induced-toxicity.html\">used Organovo’s 3D-printed human liver tissues to model drug-induced liver injury\u003C\u002Fa>. Hopes surged and enthusiastic media reports suggested that in the not-too-distant future, patients will be able to obtain artificially fabricated organs to replace defective livers, kidneys, and even hearts.\u003C\u002Fp>\n\n\n\n\u003Cp>But we have to keep in mind that for the moment, only tissues can be printed out, which function like human tissues (liver, bone, or cartilage). Organs are far away from materialising out of stem cells, we have studies and proof-of-concepts, but no actual products.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"The Bioprinting Process\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fs3CiJ26YS_U?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>By avoiding unnecessary hype, we could prepare society for these amazing technologies in a way that we don’t put impossible pressure on the shoulders of innovators and companies. \u003C\u002Fp>\n\n\n\n\u003Cp>We also have to be realistic when looking at disruptive technologies. This might be the most difficult since news about great healthcare solutions can blow our minds every single day. To not live in science fiction, we need to be cautious and conscious.\u003C\u002Fp>\n",false,{"rendered":20,"protected":18},"\u003Cp>Take a look at the most overhyped technologies in healthcare and keep in mind the realistic development opportunities in healing.\u003C\u002Fp>\n",6,21905,"closed",true,"","standard",{"_acf_changed":18,"footnotes":25},[29],521,[31,32,33,34,35,36,37],377,445,453,517,549,551,130,[39,40],949,950,[],[43,44,45,46,47,48,49,50,51,52,53,54],1683,1713,1723,1725,1731,2923,3333,4491,4859,1571,4891,1621,[56,12,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71],"post-13949","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-future-medicine","tag-robotics-2","tag-virtual-reality","tag-wearables-2","tag-gc1","tag-hype","tag-organs","tag-3d-printing-2","project_category-educators","project_category-medical-professionals",{"id":22,"alt_text":73,"caption":25,"description":73,"media_type":74,"media_details":75,"post":109,"source_url":110},"TMF, radar, buzzword","image",{"width":76,"height":77,"file":78,"sizes":79,"image_meta":106},1920,1080,"2018\u002F09\u002F033_buzzworld.gif",{"medium":80,"large":86,"thumbnail":91,"medium_large":95,"1536x1536":96,"large_old_512x288":101},{"file":81,"width":82,"height":83,"mime-type":84,"source_url":85},"033_buzzworld-370x208.gif",370,208,"image\u002Fgif","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld-370x208.gif",{"file":87,"width":88,"height":89,"mime-type":84,"source_url":90},"033_buzzworld-768x432.gif",768,432,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld-768x432.gif",{"file":92,"width":93,"height":93,"mime-type":84,"source_url":94},"033_buzzworld-150x150.gif",150,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld-150x150.gif",{"file":87,"width":88,"height":89,"mime-type":84,"source_url":90},{"file":97,"width":98,"height":99,"mime-type":84,"source_url":100},"033_buzzworld-1536x864.gif",1536,864,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld-1536x864.gif",{"file":102,"width":103,"height":104,"mime-type":84,"source_url":105},"033_buzzworld-512x288.gif",512,288,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld-512x288.gif",{"aperture":107,"credit":25,"camera":25,"caption":25,"created_timestamp":107,"copyright":25,"focal_length":107,"iso":107,"shutter_speed":107,"title":25,"orientation":107,"keywords":108},"0",[],null,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F09\u002F033_buzzworld.gif",{"cta_type":112,"cta_color":25,"subtitle":25,"related_books":113,"related_posts_footer":117,"related_posts":18,"key_takeaways":121},"subscribe",[114,115,116],24759,52203,34151,[118,119,120],53645,24598,27125,[122,124],{"title":123},"\u003Cp>The most important rule is if something sounds too good to be true in medicine, extreme caution and clear evidence are required before spreading the word about it since giving false hope is dangerous.\u003C\u002Fp>\n",{"title":125},"\u003Cp>It’s easy to find mindblowing concepts, studies, results and promises in medicine every day. Optimism is great, but over-hype can actually damage viable, important endeavors.\u003C\u002Fp>\n",{"yoast_wpseo_title":127,"yoast_wpseo_metadesc":128,"yoast_wpseo_canonical":13},"The Most Overhyped Technologies in Healthcare - The Medical Futurist","Take a look at the most overhyped technologies in healthcare and keep in mind the realistic development opportunities in healing.",{"self":130,"collection":136,"about":139,"author":142,"replies":145,"version-history":148,"predecessor-version":152,"wp:featuredmedia":156,"wp:attachment":159,"wp:term":162,"curies":178},[131],{"href":132,"targetHints":133},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F13949",{"allow":134},[135],"GET",[137],{"href":138},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[140],{"href":141},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[143],{"embeddable":24,"href":144},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[146],{"embeddable":24,"href":147},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=13949",[149],{"count":150,"href":151},54,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F13949\u002Frevisions",[153],{"id":154,"href":155},58495,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F13949\u002Frevisions\u002F58495",[157],{"embeddable":24,"href":158},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F21905",[160],{"href":161},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=13949",[163,166,169,172,175],{"taxonomy":164,"embeddable":24,"href":165},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=13949",{"taxonomy":167,"embeddable":24,"href":168},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=13949",{"taxonomy":170,"embeddable":24,"href":171},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=13949",{"taxonomy":173,"embeddable":24,"href":174},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=13949",{"taxonomy":176,"embeddable":24,"href":177},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=13949",[179],{"name":180,"href":181,"templated":24},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[183],{"id":120,"date":184,"date_gmt":185,"guid":186,"modified":188,"modified_gmt":189,"slug":190,"status":11,"type":12,"link":191,"title":192,"content":194,"excerpt":196,"author":198,"featured_media":199,"comment_status":23,"ping_status":23,"sticky":24,"template":25,"format":26,"meta":200,"categories":201,"tags":204,"project_category":211,"contact_email_category":213,"yst_prominent_words":214,"class_list":226,"better_featured_image":237,"acf":265,"yoast_meta":277,"_links":280},"2025-04-07T10:00:00","2025-04-07T08:00:00",{"rendered":187},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=27125&_wpnonce=5f715b0750&status=auto-draft&type=post","2025-04-03T15:56:50","2025-04-03T13:56:50","the-curious-case-of-a-i-discovering-unusual-associations-in-medicine","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-curious-case-of-a-i-discovering-unusual-associations-in-medicine",{"rendered":193},"AI’s Unforeseen Medical Discoveries: The Curious Case Of Unusual Associations",{"rendered":195,"protected":18},"\n\u003Cp>Artificial intelligence (AI) can do \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhats-next-for-ai-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">a plethora of astonishing things\u003C\u002Fa> in the medical space, from automating triage and administrative tasks to assisting in mental health support and medical image analysis. On top of these, every now and then, AI makes curious medical discoveries, detecting things that – to the best of our human knowledge – should not be detectable from the input data. \u003C\u002Fp>\n\n\n\n\u003Cp>These unusual associations present brand-new challenges to medical professionals who need to better understand how smart algorithms come to such conclusions that have eluded humans for decades. In this article, we consider some striking examples of AI finding connections that would otherwise remain invisible to human experts. Such observations highlight the technology’s potential and how it will continue to surprise us in the years to come.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Debiasing and speeding up radiological imaging\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>With \u003Ca href=\"https:\u002F\u002Fwww.mcpdigitalhealth.org\u002Farticle\u002FS2949-7612(24)00121-4\u002Ffulltext\" target=\"_blank\" rel=\"noreferrer noopener\">the majority of FDA-approved medical AI tools\u003C\u002Fa> targeted at radiological use, it is not surprising that the technology has found unusual associations in this field.\u003C\u002Fp>\n\n\n\n\u003Cp>In an interesting study, MIT scientists showed that deep learning algorithms \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnews.mit.edu\u002F2022\u002Fartificial-intelligence-predicts-patients-race-from-medical-images-0520\" target=\"_blank\">can predict\u003C\u002Fa> the self-reported race of patients from radiological images alone. This is a feat even the most seasoned physicians cannot do, and it’s not clear how the model was able to do this. Such insights can have practical uses as they help to \u003Ca href=\"https:\u002F\u002Fnews.mit.edu\u002F2022\u002Fartificial-intelligence-predicts-patients-race-from-medical-images-0520\" target=\"_blank\" rel=\"noreferrer noopener\">counter bias\u003C\u002Fa> inherent in medical records.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"720\" height=\"405\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F08\u002Ftmf_article_350-01_2_720.png\" alt=\"TMF AU doctor algorithm radiology digital health\" class=\"wp-image-48905\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F08\u002Ftmf_article_350-01_2_720.png 720w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F08\u002Ftmf_article_350-01_2_720-370x208.png 370w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>At UMass Memorial Health, \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">at least 40 AI tools\u003C\u002Fa> assist in clinical workflows, handling tasks such as getting results to critical patients faster and assisting in billing. They also aid in refining the quality of radiological images. This has been associated with patients spending less time in MRI machines. The scanning process is thus made more tolerable and patients feel less anxious.\u003C\u002Fp>\n\n\n\n\u003Cp>“MRIs are long, uncomfortable and loud, but they’re really valuable for medical decision making,” Dr. Elisabeth Garwood from UMass Memorial Health \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">explained\u003C\u002Fa>. “The acceleration algorithms at UMass are making our MRIs 25 percent faster, and that really hacks the patient experience that they’re in the MRI for less time.”\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Enhancing diagnoses with photos, voice recordings and breath scans\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In the digital health market, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-do-digital-biomarkers-mean\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">digital biomarkers\u003C\u002Fa>, or digital data that provide insights into an individual’s health status, are gaining popularity, but AI seem to be able to derive insights from its own unusual sources.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers \u003Ca href=\"https:\u002F\u002Fwww.mcpdigitalhealth.org\u002Farticle\u002FS2949-7612(23)00073-1\u002Ffulltext\" target=\"_blank\" rel=\"noreferrer noopener\">trained a model\u003C\u002Fa> to analyse 10-second-long voice recordings to diagnose type 2 diabetes based on certain acoustic features. While not displaying ideal performance, the model produced promising results, which were better than chance in correctly identifying diabetic individuals. This development makes the scenario of being able to detect one’s blood glucose levels from a smartphone quite plausible.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-768x432.png\" alt=\"vocal biiomarker, TMF, digital health\" class=\"wp-image-36955\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F11\u002Ftmf_article_305-01-1.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Dr. Jude Kong, who leads the Africa-Canada AI & Data Innovation Consortium and the Global South AI for Pandemic & Epidemic Preparedness & Response Network, has been collaborating with governments to \u003Ca href=\"https:\u002F\u002Fwww.newsweek.com\u002Fhealth-care-artificial-intelligence-ai-advancements-impact-awards-2034142\" target=\"_blank\" rel=\"noreferrer noopener\">employ bespoke AI tools for practical diagnoses\u003C\u002Fa> through unconventional means. \u003C\u002Fp>\n\n\n\n\u003Cp>For example, a model deployed in Ethiopia can help determine if a patient’s paralysis is indicative of polio based on a photograph. In Peru, they co-created a breathalyzer that leverages AI technology to help diagnose respiratory disease.\u003C\u002Fp>\n\n\n\n\u003Cp>Google researchers also employed AI to detect health risks from images. In particular, they \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41551-018-0195-0\" target=\"_blank\" rel=\"noreferrer noopener\">trained deep-learning models\u003C\u002Fa> to identify signs indicating long-term cardiovascular risks from retinal images.\u003C\u002Fp>\n\n\n\n\u003Cp>Traditionally, in order to assess those risks, doctors need to manually look at the retina, do blood tests and consider other factors like age and BMI. Impressively, \u003Ca href=\"https:\u002F\u002Fwww.washingtonpost.com\u002Fnews\u002Fthe-switch\u002Fwp\u002F2018\u002F02\u002F19\u002Fgoogle-used-artificial-intelligence-to-predict-heart-attacks-with-the-human-eye\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">the AI taught itself what to look for\u003C\u002Fa> in retinal images alone after having gone through enough data to identify patterns found in the eyes of people at risk.\u003C\u002Fp>\n\n\n\n\u003Cp>Such technology can prove to be lifesaving, especially considering the fact that \u003Ca href=\"https:\u002F\u002Fwww.who.int\u002Fhealth-topics\u002Fcardiovascular-diseases\" target=\"_blank\" rel=\"noreferrer noopener\">some 17 million people die of cardiovascular diseases\u003C\u002Fa> every year. It can help doctors and even patients run a quick screening test and assess their risk and take subsequent preventive actions.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Improving psychiatric care with brain waves, early Alzheimer’s detection and coma recovery assessments\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Psychiatric care stands to gain a boost thanks to the assistance of AI. As surprising as it might sound, treatment selection for antidepressants is \u003Ca href=\"https:\u002F\u002Ftime.com\u002F5786081\u002Fdepression-medication-treatment-artificial-intelligence\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">generally based on\u003C\u002Fa> trial and error. This is the reason that \u003Ca href=\"https:\u002F\u002Fajp.psychiatryonline.org\u002Fdoi\u002F10.1176\u002Fappi.ajp.163.1.5\" target=\"_blank\" rel=\"noreferrer noopener\">only 30% of patients\u003C\u002Fa> respond well to the first antidepressant prescribed, but the input of AI can provide a more effective method. \u003C\u002Fp>\n\n\n\n\u003Cp>By studying the brainwaves of patients, researchers \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41587-019-0397-3#author-information\" target=\"_blank\" rel=\"noreferrer noopener\">used a machine learning algorithm\u003C\u002Fa> to identify the best antidepressant: sertaline, in this case. Their results showed that 65% of patients with a particular brainwave pattern indicated a strong response to sertraline. One of the researchers suggested that this method is “far better” than relying on clinical factors, such as certain symptoms, to try to guess whether a drug will have a favourable effect on patients.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"720\" height=\"405\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png\" alt=\"fake drugs counterfeit medicine\" class=\"wp-image-40965\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png 720w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2-370x208.png 370w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>For a condition like Alzheimer’s, patients are commonly diagnosed with the condition after the symptoms manifest. These can be very debilitating, such as memory loss, personality changes and depression. A research team at the University of California in San Francisco trained an algorithm to look for indicative signs of Alzheimer’s from another angle.\u003C\u002Fp>\n\n\n\n\u003Cp>The researchers \u003Ca href=\"https:\u002F\u002Fmedicalxpress.com\u002Fnews\u002F2018-11-artificial-intelligence-alzheimer-years-diagnosis.html\" target=\"_blank\" rel=\"noreferrer noopener\">trained a deep learning algorithm on FDG-PET scans\u003C\u002Fa>, a method used to study the metabolic activity of brain cells. This taught the AI to recognise metabolic patterns associated with Alzheimer’s disease. In subsequent tests, the AI detected the condition with 100% sensitivity, on average more than six years prior to the final diagnosis!\u003C\u002Fp>\n\n\n\n\u003Cp>Being in a coma or vegetative state can be one of the most ethically-taxing issues in healthcare. Based on doctors’ recommendations, relatives of such patients can decide if they would like to terminate life support. It’s a highly debatable issue what the decision will prolong: the patient’s life or suffering, while also costing both the relatives and the healthcare system. However, AI can aid in making more informed decisions in these cases, correctly predicting if one will regain consciousness even after doctors conclude an unlikely recovery.\u003C\u002Fp>\n\n\n\n\u003Cp>Such an AI system has been developed by the Chinese Academy of Sciences and PLA General Hospital in Beijing. Their algorithm \u003Ca href=\"https:\u002F\u002Fwww.scmp.com\u002Fnews\u002Fchina\u002Fscience\u002Farticle\u002F2163298\u002Fdoctors-said-coma-patients-would-never-wake-ai-said-they-would\" target=\"_blank\" rel=\"noreferrer noopener\">reportedly achieved about 90 percent accuracy\u003C\u002Fa> on prognostic assessments. The software analyzes brain scans to re-evaluate doctor’s decisions. In at least 7 cases where doctors were confident that patients wouldn’t regain consciousness, the AI contradicted them and indeed those patients woke up within 12 months of the brain scans. “Our machine can ‘see’ things invisible to human eyes,” \u003Ca href=\"https:\u002F\u002Fwww.scmp.com\u002Fnews\u002Fchina\u002Fscience\u002Farticle\u002F2163298\u002Fdoctors-said-coma-patients-would-never-wake-ai-said-they-would\" target=\"_blank\" rel=\"noreferrer noopener\">Dr Song Ming, first author of the study, said\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>This is because the evaluation of patients is done using a brain scan with functional magnetic resonance imaging and the rapidly evolving neural activities can prove challenging for doctors to detect. On the other hand, a machine learning algorithm can detect minute changes indicative of an ongoing recovery. This could help doctors and relatives make more informed decisions when it comes to such patients.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Aiding the identification and treatment of rare diseases\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>If a disease is rare, then its identification and treatment will pose a challenge. Yearly, about half a million children are born with a rare hereditary disease around the world. However, many of these cases present with specific physical features that can help in their identification. Clinicians might miss these due to the fact that they’ve never seen such cases. In addition, due to the rarity of such cases, treatment options are often poorly understood. However, nothing escapes the meticulous eye of AI.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers from the University of Pennsylvania used a predictive AI tool to identify a suitable medicine to \u003Ca href=\"https:\u002F\u002Fwww.pennmedicine.org\u002Fnews\u002Fnews-releases\u002F2025\u002Ffebruary\u002Fai-tool-helps-find-life-saving-medicine-for-rare-disease\" target=\"_blank\" rel=\"noreferrer noopener\">save the life of a patient\u003C\u002Fa> with idiopathic multicentric Castleman’s disease (iMCD). This rare condition is characterised by a poor survival rate and a lack of treatment. \u003C\u002Fp>\n\n\n\n\u003Cp>But after analysing thousands of existing medications, the AI system predicted that an FDA-approved monoclonal antibody used to treat other conditions would likely work for iMCD; and it did. The patient is now almost two years into remission, and this approach could also be applicable to other rare diseases.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-768x432.png\" alt=\"\" class=\"wp-image-50863\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_362_AI_doctor_robot.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Researchers based in Germany \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41436-019-0566-2\" target=\"_blank\" rel=\"noreferrer noopener\">developed and trained an algorithm\u003C\u002Fa> to help the identification of diseases caused by a change in a single gene. These include conditions like mucopolysaccharidosis, Mabry syndrome and Kabuki syndrome, where those affected have characteristic facial features.\u003C\u002Fp>\n\n\n\n\u003Cp>The researchers trained the neural network DeepGestalt with 30,000 portrait photos of those with such rare conditions. “In combination with facial analysis, it is possible to filter out the decisive genetic factors and prioritize genes,” \u003Ca href=\"https:\u002F\u002Fwww.sciencedaily.com\u002Freleases\u002F2019\u002F06\u002F190606133805.htm\" target=\"_blank\" rel=\"noreferrer noopener\">said Prof. Krawitz\u003C\u002Fa> who worked on this study. “Merging data in the neuronal network reduces data analysis time and leads to a higher rate of diagnosis.”\u003C\u002Fp>\n\n\n\n\u003Cp>Their results showed that with the help of AI, identifying rare diseases was much more accurate. Using this technique could fast-track the identification and treatment of those affected from early on.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Synchronising surgical rooms\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>While there is a promising \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-technological-future-of-surgery\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">technological future of surgery\u003C\u002Fa>, the focus is mostly on assisting surgeons instead of the whole surgical team working behind the scenes of procedures.  To enhance the collaboration and synchronicity of surgical teams, \u003Ca href=\"https:\u002F\u002Fexex.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">startup eXeX\u003C\u002Fa> has developed a dedicated AI platform. It leverages the Apple Vision Pro headset to improve communication, clarity and orientation within the surgical suite.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png\" alt=\"\" class=\"wp-image-34403\" width=\"768\" height=\"432\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Their product combines a language model with a computer vision model to assist the surgical teams in answering questions during a procedure and help them orient themselves in the room. \u003C\u002Fp>\n\n\n\n\u003Cp>“The app running on the headset has a full spatial awareness in the room in real time, and it understands exactly where the user is and even knows what the user is looking at,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fexex.ai\u002F\" target=\"_blank\">explained Nicholas Cambata\u003C\u002Fa>, COO of eXeX. For example, a surgical assistant could set up a tray prior to a procedure and request a check from the AI. The tool can identify any missing equipment and guide the user to the exact location in the room.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Points system to assess one’s need for hospitalization\u003C\u002Fh2>\n\n\n\n\u003Cp>This was the premise of \u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\">a pilot \u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">p\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.zdnet.com\u002Farticle\u002Fai-in-healthcare-using-algorithms-to-predict-your-risk-of-ending-up-in-hospital\u002F\">roject\u003C\u002Fa> from Bering Research and GPs at Axbridge Surgery in Somerset, England. An algorithm was deployed to predict which patients might need to be admitted to a hospital and to help GPs work on reducing the risk.\u003C\u002Fp>\n\n\n\n\u003Cp>The AI allocates points, based on a percentage scale, according to underlying health conditions and contributing factors like elevated blood pressure or smoking habits. The higher the points, the more likely the patient will need hospitalization.\u003C\u002Fp>\n\n\n\n\u003Cp>The aim is to have GPs intervene earlier, make accurate predictions on hospital admissions, and help hospitals plan on allocating their resources.\u003C\u002Fp>\n\n\n\n\u003Cp>While these unusual associations give a glimmer of hope to millions of patients around the world, we must be cautious about how we take this news. The experiments conducted need to be validated and repeated on a larger scale while considering other contributing factors like comorbidities.\u003C\u002Fp>\n\n\n\n\u003Cp>However, it does show that artificial intelligence can become an integral part of not only treating patients but also identifying risks, and taking preventive measures we have never thought about before.\u003C\u002Fp>\n",{"rendered":197,"protected":18},"\u003Cp>Determining patients’ race from chest x-rays alone or diagnosing type 2 diabetes from short audio samples. AI can do it and we don’t know how. There are fascinating examples of unusual associations.\u003C\u002Fp>\n",16,27237,{"_acf_changed":18,"footnotes":25},[202,203],7079,504,[205,206,207,208,209,210],144,207,275,313,425,134,[39,40,212],951,[],[215,216,217,218,219,220,221,222,223,224,225],1631,1715,1789,1833,2717,2719,2737,2741,2747,2755,1587,[227,12,57,58,59,60,61,228,229,230,231,232,233,234,235,70,71,236],"post-27125","category-tmf","category-artificial-intelligence","tag-artificial-intelligence","tag-digital-health","tag-healthcare","tag-medicine","tag-technology-2","tag-ai","project_category-patients",{"id":199,"alt_text":238,"caption":25,"description":25,"media_type":74,"media_details":239,"post":120,"source_url":264},"AI association",{"width":76,"height":77,"file":240,"sizes":241,"image_meta":263},"2020\u002F03\u002FAI-association-small.jpg",{"medium":242,"large":248,"thumbnail":253,"medium_large":257,"1536x1536":258},{"file":243,"width":244,"height":245,"mime-type":246,"source_url":247},"AI-association-small-370x208.jpg","370","208","image\u002Fjpeg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-370x208.jpg",{"file":249,"width":250,"height":251,"mime-type":246,"source_url":252},"AI-association-small-768x432.jpg","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-768x432.jpg",{"file":254,"width":255,"height":255,"mime-type":246,"source_url":256},"AI-association-small-150x150.jpg","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-150x150.jpg",{"file":249,"width":250,"height":251,"mime-type":246,"source_url":252},{"file":259,"width":260,"height":261,"mime-type":246,"source_url":262},"AI-association-small-1536x864.jpg","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-1536x864.jpg",{"aperture":107,"credit":25,"camera":25,"caption":25,"created_timestamp":107,"copyright":25,"focal_length":107,"iso":107,"shutter_speed":107,"title":25,"orientation":107},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small.jpg",{"cta_type":112,"cta_color":25,"subtitle":25,"related_books":266,"related_posts_footer":269,"related_posts":18,"key_takeaways":272},[267,268,115],24762,24761,[118,270,271],53187,52901,[273,275],{"title":274},"\u003Cp>Artificial intelligence has wide-ranging applications in medical practice, but the technology continues to surprise in novel ways.\u003C\u002Fp>\n",{"title":276},"\u003Cp>In this article, we uncover some unusual medical associations made with AI that would otherwise remain oblivious to human eyes.\u003C\u002Fp>\n",{"yoast_wpseo_title":278,"yoast_wpseo_metadesc":279,"yoast_wpseo_canonical":191},"AI's Unforeseen Medical Discoveries: Unusual Associations","AI has amazing medical discoveries, and sometimes we don't know how it came to the correct results as the input data seems insufficient for humans.",{"self":281,"collection":286,"about":288,"author":290,"replies":293,"version-history":296,"predecessor-version":300,"wp:featuredmedia":304,"wp:attachment":307,"wp:term":310,"curies":321},[282],{"href":283,"targetHints":284},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F27125",{"allow":285},[135],[287],{"href":138},[289],{"href":141},[291],{"embeddable":24,"href":292},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[294],{"embeddable":24,"href":295},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=27125",[297],{"count":298,"href":299},39,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F27125\u002Frevisions",[301],{"id":302,"href":303},58663,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F27125\u002Frevisions\u002F58663",[305],{"embeddable":24,"href":306},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F27237",[308],{"href":309},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=27125",[311,313,315,317,319],{"taxonomy":164,"embeddable":24,"href":312},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=27125",{"taxonomy":167,"embeddable":24,"href":314},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=27125",{"taxonomy":170,"embeddable":24,"href":316},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=27125",{"taxonomy":173,"embeddable":24,"href":318},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=27125",{"taxonomy":176,"embeddable":24,"href":320},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=27125",[322],{"name":180,"href":181,"templated":24},[324],{"id":116,"date":325,"date_gmt":326,"guid":327,"modified":329,"modified_gmt":330,"slug":331,"status":11,"type":332,"link":333,"title":334,"content":336,"excerpt":338,"author":21,"featured_media":340,"comment_status":23,"ping_status":23,"template":25,"yst_prominent_words":341,"class_list":342,"better_featured_image":345,"acf":364,"yoast_meta":384,"_links":387},"2021-04-29T10:56:15","2021-04-29T08:56:15",{"rendered":328},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=34151","2023-03-12T17:57:15","2023-03-12T16:57:15","top-20-digital-health-trends-for-the-near-future","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Ftop-20-digital-health-trends-for-the-near-future\u002F",{"rendered":335},"Top 20 Digital Health Trends For The Near Future",{"rendered":337,"protected":18},"\n\u003Cp>Digital technology could help transform unsustainable healthcare systems, provide cheaper, faster, and more effective solutions for diseases – and could lead to healthier individuals living in healthier communities.\u003C\u002Fp>\n\n\n\n\u003Cp>In this book, we analyze the top 20 trends shaping the future of healthcare, and what they all look like in practice.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003C\u002Fp>\n",{"rendered":339,"protected":18},"\u003Cp>Digital technology could help transform unsustainable healthcare systems, provide cheaper, faster, and more effective solutions for diseases – and could lead to healthier individuals living 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in on 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