[{"data":1,"prerenderedAt":437},["ShallowReactive",2],{"slug-data-annotation":3},{"post":4,"relatedPosts":192,"relatedBooks":340},{"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,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":33,"project_category":50,"contact_email_category":51,"yst_prominent_words":52,"class_list":63,"better_featured_image":88,"acf":120,"yoast_meta":137,"_links":139},23557,"2026-08-31T09:17:48","2026-08-31T07:17:48",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=23557&_wpnonce=1a0155603d&status=auto-draft&type=post","2026-08-31T09:17:49","2026-08-31T07:17:49","data-annotation","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fdata-annotation",{"rendered":17},"Data Annotators: The Unsung Heroes Of Artificial Intelligence Development",{"rendered":19,"protected":20},"\n\u003Cp>The wonders of AI in healthcare are undeniable, revolutionising diagnostics and prevention with astonishing advancements. From \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fabout.google\u002Fstories\u002Fseeingpotential\u002F\" target=\"_blank\">detecting diabetic retinopathy\u003C\u002Fa> to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-2023-skin-checking-apps-landscape-infographic\u002F\" target=\"_blank\">algorithms identifying skin cancer\u003C\u002Fa>, and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC9947926\u002F\" target=\"_blank\">predicting cardiovascular risks\u003C\u002Fa>, AI’s achievements are reshaping patient care. \u003C\u002Fp>\n\n\n\n\u003Cp>But underpinning these headline-grabbing breakthroughs is an invisible army whose meticulous work powers the algorithms that save lives. They’re the unsung heroes of the AI healthcare revolution, often underpaid and underappreciated. So, who are these hidden figures? What exactly do they do? \u003C\u002Fp>\n\n\n\n\u003Cp>Have you ever wondered how to create a smart algorithm? Where and how do you get the data for it? What makes a pattern-recognizing program work well and what are the challenges? Nowadays, everyone seems to be building artificial intelligence-based software, also in healthcare. Still, no one talks about one of the most important aspects of the work: \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fjmai.amegroups.org\u002Farticle\u002Fview\u002F5208\u002Fhtml\" target=\"_blank\">data annotation and the people who do this time-consuming, rather monotonous task\u003C\u002Fa> without the flare that usually encircles AI. \u003C\u002Fp>\n\n\n\n\u003Cp>Without their dedicated work, it is impossible to develop algorithms, so we all need to know and talk about the superheroes of algorithm development: data annotators.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>How to make algorithms dream of cats?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The method for creating and teaching an algorithm depends on the question it aims to solve. Let’s say you want the algorithm to spot lung tumors in chest X-rays. For that, you will need tools for pattern recognition – the question doesn’t differ much from spotting cats on Instagram. \u003C\u002Fp>\n\n\n\n\u003Cp>At first, it sounds easy. Until you start thinking about how to explain to a computer what a cat is. Our usual human clues – fur, ears, eyes, whiskers, four legs, cuteness, and grace – mean nothing to an algorithm that only sees pixels.\u003C\u002Fp>\n\n\n\n\u003Cp>“You will need millions of cat photos, appropriately labeled as having a cat. That way, a neural network or a multilayered deep neural network can be trained using supervised learning to recognize pictures with cats in them”, David Albert, M.D., Founder and Chief Medical Officer of AliveCor of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.alivecor.com\u002F\" target=\"_blank\">AliveCor\u003C\u002Fa>, the company that has been developing a medical-grade, pocket-sized device to measure EKG anywhere in less than 30 seconds, explained The Medical Futurist. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"439\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-dzZs0UDERvVp90TBU2KldcHp-768x439.jpg\" alt=\"\" class=\"wp-image-55175\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-dzZs0UDERvVp90TBU2KldcHp-768x439.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-dzZs0UDERvVp90TBU2KldcHp-1536x878.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-dzZs0UDERvVp90TBU2KldcHp.jpg 1792w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">ChatGPT’s idea of a cat studying medicine\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>So, you won’t tell the algorithm what’s a cat, but you rather show it millions of examples to help it figure it out by itself. That’s why data and data annotation is critical for building smart algorithms. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What is data annotation?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Annotating data is time-consuming and tedious without any of the flare promised by artificial intelligence associated with sci-fi-like thinking and talking computers or robots. In healthcare, the creation of algorithms is rather about utilizing existing databases which mainly encompass imaging files, CT or MR scans, samples used in pathology, etc. At the same time, data annotation will be drawing lines around tumors, pinpointing cells or designating ECG rhythm strips. Thousands, tens of thousands of them. No magic, no self-aware computers.\u003C\u002Fp>\n\n\n\n\u003Cp>That’s what Dr. Albert has been doing. “\u003Cem>You need accurately labeled and annotated data to develop these deep neural diagnostic solutions. But it’s an awful lot of work.\u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>For example, I may annotate or diagnose ten thousand ECGs over several weeks, then another expert goes through the same ten thousand – and then we see where we disagree. After that, we have a third person, who is the adjudicator – who comes in and says, okay, regarding this five hundred where you disagree, this is what I think the answer is. \u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>So it takes at least three people and weeks of work to give you a reasonably confident answer. Deep neural networks to perform correctly in order to take advantage of big data require a tremendous amount of annotation work”.\u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"850\" height=\"255\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002FECG-Strip-with-annotations-visible-5-seconds-of-data.png\" alt=\"data annotation\" class=\"wp-image-23562\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002FECG-Strip-with-annotations-visible-5-seconds-of-data.png 850w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002FECG-Strip-with-annotations-visible-5-seconds-of-data-768x230.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002FECG-Strip-with-annotations-visible-5-seconds-of-data-512x154.png 512w\" sizes=\"auto, (max-width: 850px) 100vw, 850px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">1 ECG Strip with annotations visible (5 seconds of data). Source: www.researchgate.net\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Counting\ncells and drawing precise lines around tumors\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Katharina von Loga is a consultant pathologist at The Royal Marsden NHS Foundation Trust. A while ago she explained how she uses software-based image analysis to monitor the changes of immune cells within cancerous tumors during therapy. The computer helps her count the cells after she designates carefully the set of cells she’s looking for. \u003C\u002Fp>\n\n\n\n\u003Cp>“\u003Cem>I have an image of a stain in front of me, where I can click on the specific set and annotate that that’s a tumor cell. Then I click on another cell and say that’s a subtype of an immune cell. It needs a minimum of all the different types I specified, only after that can I apply it to the whole image. Then I look at the output to see if I agree with the ones that I didn’t annotate but the computer classified. That’s the process you can do indefinitely\u003C\u002Fem>,” she explained. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The hardships of data annotation\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Although it sounds perfect in theory that you can train an algorithm to support medical work in pathology, the practice is much more complicated. As medical data archives were (obviously) not created with mathematical algorithms in mind, it’s gargantuan work to standardize existing sampling processes or to have enough “algorithm-adjusted” samples. \u003C\u002Fp>\n\n\n\n\u003Cp>It matters how the sample was processed from getting the specimen from the patient until it’s under the microscope. The staining method, the age of the sample, the department where the sample was produced – are all factors to count when deciding on a sample for successful algorithmic teaching.\u003C\u002Fp>\n\n\n\n\u003Cp>Beyond the problems of the massive variability in the samples, we have another issue: the lack of experts for data annotation, as well as the difficulty of finding databases of scale. Usually, the precision of an algorithm depends on the size of the sample – the bigger, the better. However, hospitals or medical centers, even really resourceful ones, don’t have enough data or enough annotations. It takes companies like Google, Amazon, or Tencent with unlimited financial resources and a global footprint to derive the kind of scale that you need to develop accurate AI.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"439\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002FAnnotated-medical-data-768x439.jpg\" alt=\"\" class=\"wp-image-55197\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002FAnnotated-medical-data-768x439.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002FAnnotated-medical-data-1536x878.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002FAnnotated-medical-data.jpg 1792w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">ChatGPT’s idea of a data annotator\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>What is more, the human resources problem is aggravating. There are only 30-35,000 cardiologists in the United States, all very busy. They don’t have time to mark ECGs. On the same note, there are only about 50,000 radiologists – they don’t have time to read more chest X-rays. So, we have to do something. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>From medical students through online annotators to AI building its own AI\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Experts often mention the option to employ medical students or pre-med students in university for simpler annotation tasks – to at least solve the human resources trouble. David Albert played with the thought of building online courses for training prospective annotators, who would afterward get some financial incentives for the annotation of millions of data points. Medical facilities could basically crowdsource data annotation through platforms such as \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.mturk.com\u002F\" target=\"_blank\">Amazon Mechanical Turk\u003C\u002Fa>. The process could employ the “wisdom of the crowds”. \u003C\u002Fp>\n\n\n\n\u003Cp>Another option would be the employment of algorithms also for annotation tasks – so basically building AI for teaching another smart software. We’ve seen deep learning-based tools that can do completely automatic annotation by themselves and then the user just has to correct where this automatic process did not work well. \u003C\u002Fp>\n\n\n\n\u003Cp>Katharina von Loga also mentioned how international and national committees are working on the standardization of the various sampling processes, which could really ease annotation work and accelerate the building of algorithms. All these could lead to better and bigger datasets, more optimised data annotation and more efficient AI in every medical subfield. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What will the future bring for smart algorithms in\nhealthcare?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>We’ll see the widespread appearance of smart algorithms in the next five to ten years. We will have much more sophisticated artificial intelligence for healthcare. It would augment doctors and allow them to return to being physicians, not just documenters. We all know how administrative tasks considerably add to the \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fphysician-burnout\">problem of physician burnout\u003C\u002Fa>, thus such AI solutions are much needed. \u003C\u002Fp>\n\n\n\n\u003Cp>Artificial intelligence will not replace physicians, the combination of their work with that of fellow medical professionals should be the direction to take for the future. However, we also see that doctors who don’t use algorithms might get replaced by the ones who do so. \u003C\u002Fp>\n\n\n\n\u003Cp>While there will be (and should be) countless debates about the ways of cooperation between artificial intelligence and physicians, one thing is certainly clear. We will never have smart algorithms in healthcare without data annotators. \u003C\u002Fp>\n\n\n\n\u003Cp>That’s why we felt the need to talk about and appreciate the experts who right now might be sitting in dark hospital rooms in front of computers and annotating radiology or ophthalmology images so someone else somewhere else could create a potentially lifesaving medical application from them. Without the data annotation heroes, we’ll never have artificial intelligence in healthcare.\u003C\u002Fp>\n\n\n\n\u003Cp>Kudos to all data annotators out there!\u003C\u002Fp>\n\n\n\n\u003Ctable style=\"width: 100%; border-collapse: collapse; background-color: #eee; border-top: 4px solid #444;\" cellpadding=\"10px\">\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd style=\"width: 100%;\">\n\u003Cp>\u003Cstrong>At The Medical Futurist, we are building a community for making a bold vision about the future of healthcare reality today.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ciframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FFIbMejImnxs\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen=\"\">\u003C\u002Fiframe>\n\u003Cp>If you’d like to support this mission, we invite you to \u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">join The Medical Futurist Patreon Community\u003C\u002Fa>. A community of empowered patients, future-oriented healthcare professionals, concerned health policymakers, sensible health tech developers, and enthusiastic medical students. If there were ever a time to join us, it is now. Every contribution, however big or small, powers our research and sustains our future.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">\u003Cstrong style=\"background-color: #e71d3299; color: #000;\">Click here to support The Medical Futurist from as little as $3\u003C\u002Fstrong>\u003C\u002Fa> – it only takes a minute. Thank you.\u003C\u002Fp>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\u003Cp> \u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>We hear a lot about AI, but almost nothing about the work essential for the healthcare AI revolution: labeling and annotating data so algorithms can learn from it. Who does it? How? Why? Let’s see!\u003C\u002Fp>\n",6,23566,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32],504,521,[34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],137,144,196,1168,214,1228,246,1297,247,1298,271,275,313,358,134,425,[],[],[53,54,55,56,57,58,59,60,61,62],1819,1833,1883,2689,5393,1683,1693,1715,1723,1741,[64,14,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87],"post-23557","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-future-medicine","tag-algorithm","tag-artificial-intelligence","tag-data-2","tag-smart-algorithm","tag-doctor","tag-artificial","tag-future","tag-data-annotation","tag-future-of-medicine","tag-annotation","tag-health","tag-healthcare","tag-medicine","tag-physician","tag-ai","tag-technology-2",{"id":24,"alt_text":89,"caption":27,"description":27,"media_type":90,"media_details":91,"post":5,"source_url":119},"data annotation","image",{"width":92,"height":93,"file":94,"sizes":95,"image_meta":117},1920,1080,"2019\u002F04\u002F081_data_annotator-scaled.png",{"medium":96,"large":102,"thumbnail":107,"medium_large":111,"1536x1536":112},{"file":97,"width":98,"height":99,"mime-type":100,"source_url":101},"081_data_annotator-scaled-370x208.png","370","208","image\u002Fpng","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F081_data_annotator-scaled-370x208.png",{"file":103,"width":104,"height":105,"mime-type":100,"source_url":106},"081_data_annotator-scaled-768x432.png","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F081_data_annotator-scaled-768x432.png",{"file":108,"width":109,"height":109,"mime-type":100,"source_url":110},"081_data_annotator-scaled-150x150.png","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F081_data_annotator-scaled-150x150.png",{"file":103,"width":104,"height":105,"mime-type":100,"source_url":106},{"file":113,"width":114,"height":115,"mime-type":100,"source_url":116},"081_data_annotator-scaled-1536x864.png","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F081_data_annotator-scaled-1536x864.png",{"aperture":118,"credit":27,"camera":27,"caption":27,"created_timestamp":118,"copyright":27,"focal_length":118,"iso":118,"shutter_speed":118,"title":27,"orientation":118},"0","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F081_data_annotator-scaled.png",{"related_posts":20,"related_posts_footer":121,"cta_type":125,"cta_color":27,"subtitle":27,"related_books":126,"key_takeaways":130},[122,123,124],55115,55033,54887,"books",[127,128,129],52203,24761,24759,[131,133,135],{"title":132},"\u003Cp>Artificial Intelligence (AI) is transforming healthcare diagnostics and prevention, with significant advancements in detecting diseases like diabetic retinopathy and skin cancer.\u003C\u002Fp>\n",{"title":134},"\u003Cp>The success of AI in healthcare is largely attributable to the meticulous work of data annotators, who label and prepare datasets for AI training, yet their crucial contributions often go unrecognized and underappreciated.\u003C\u002Fp>\n",{"title":136},"\u003Cp>Despite their fundamental role in AI development, data annotators face challenges such as inadequate compensation and lack of recognition, highlighting the need for greater acknowledgment of their contributions to healthcare innovations.\u003C\u002Fp>\n",{"yoast_wpseo_title":17,"yoast_wpseo_metadesc":138,"yoast_wpseo_canonical":15},"Without data annotation, it's impossible to develop AI, so we thought it was time to sing an ode to the superheroes of algorithm development: annotators.",{"self":140,"collection":146,"about":149,"author":152,"replies":155,"version-history":158,"predecessor-version":162,"wp:featuredmedia":166,"wp:attachment":169,"wp:term":172,"curies":188},[141],{"href":142,"targetHints":143},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F23557",{"allow":144},[145],"GET",[147],{"href":148},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[150],{"href":151},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[153],{"embeddable":26,"href":154},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[156],{"embeddable":26,"href":157},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=23557",[159],{"count":160,"href":161},28,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F23557\u002Frevisions",[163],{"id":164,"href":165},55377,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F23557\u002Frevisions\u002F55377",[167],{"embeddable":26,"href":168},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F23566",[170],{"href":171},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=23557",[173,176,179,182,185],{"taxonomy":174,"embeddable":26,"href":175},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=23557",{"taxonomy":177,"embeddable":26,"href":178},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=23557",{"taxonomy":180,"embeddable":26,"href":181},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=23557",{"taxonomy":183,"embeddable":26,"href":184},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=23557",{"taxonomy":186,"embeddable":26,"href":187},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=23557",[189],{"name":190,"href":191,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[193],{"id":124,"date":194,"date_gmt":195,"guid":196,"modified":198,"modified_gmt":199,"slug":200,"status":13,"type":14,"link":201,"title":202,"content":204,"excerpt":206,"author":23,"featured_media":208,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":209,"categories":210,"tags":213,"project_category":216,"contact_email_category":220,"yst_prominent_words":221,"class_list":230,"better_featured_image":239,"acf":280,"yoast_meta":296,"_links":298},"2026-07-14T09:34:40","2026-07-14T07:34:40",{"rendered":197},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=54887&_wpnonce=0ec9f39f0d&status=auto-draft&type=post","2026-07-14T09:34:41","2026-07-14T07:34:41","digital-health-menopause-and-the-150-billion-ignorance","https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-health-menopause-and-the-150-billion-ignorance",{"rendered":203},"Digital Health, Menopause, And The $150 Billion Ignorance",{"rendered":205,"protected":20},"\n\u003Cp>The idea of this story came from personal experience. During the past year, I have spent countless hours and a bucketload of money trying to figure out what the heck is wrong with my health. I was feeling worse and worse, having various symptoms, totally inexplicable with my impeccable test results. During this journey, not a single doctor asked or suggested that my symptoms may come from entering perimenopause – the stage of life of women preceding menopause. \u003C\u002Fp>\n\n\n\n\u003Cp>I am 47 years old, and as I have learned since then, extremely average in starting to have perimenopause symptoms at the age of 47. Also very average with the specific symptoms I have. And even more average in entering this phase of my life with zero practical knowledge or info about the possible symptoms, and treatment options. As it turns out, an overwhelming majority, \u003Ca href=\"https:\u002F\u002Fwww.ucl.ac.uk\u002Fnews\u002F2023\u002Fapr\u002Fnine-ten-women-were-never-educated-about-menopause\" target=\"_blank\" rel=\"noreferrer noopener\">about 90% of women\u003C\u002Fa> report the same. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">A loss of $150 billion every year\u003C\u002Fh2>\n\n\n\n\u003Cp>Perimenopause and menopause have lasting health implications that profoundly impact our aging process – how we retain strength, mobility, and cognitive abilities. This isn’t an issue confined to a few years, it impacts all women over 45 – that’s roughly 1.2 billion people worldwide, about 30% of the living female population till the end of their lives. And around 40% in developed nations where lifespans are longer.\u003C\u002Fp>\n\n\n\n\u003Cp>Even if we don’t care about the “subjective” factors, like women feeling terrible and getting osteoporosis, hard economic reasoning also dictates that humanity should tackle the issue of (peri)menopause. The annual global economic impact from productivity loss and healthcare costs is estimated at $150 billion, \u003Ca href=\"https:\u002F\u002Fwww.bloomberg.com\u002Fnews\u002Farticles\u002F2021-06-18\u002Fwomen-are-leaving-the-workforce-for-a-little-talked-about-reason\" target=\"_blank\" rel=\"noreferrer noopener\">Bloomberg reported\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>Despite menopause’s far-reaching consequences, funding for medical research in this area is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ffinance.yahoo.com\u002Fnews\u002Fmenopause-600-billion-opportunity-report-110019808.html\" target=\"_blank\">shockingly scarce\u003C\u002Fa>. Of the $254 million invested in women’s health technology over the past decade, a mere 5% has been allocated to menopause treatments. Most funds were prioritized for reproductive health and fertility. We \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Funderfunding-research-of-female-health-leaves-huge-amounts-of-money-on-the-table\u002F\" target=\"_blank\">have already analysed\u003C\u002Fa> how underfunded female health issues \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fd41586-023-01472-5\">are in general\u003C\u002Fa>, menopause is a great example. \u003C\u002Fp>\n\n\n\n\u003Cp>Dr. Mary Clair Haver, an American OB-GYN specializing in menopause revealed a \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=oQqcnYcKx68\" target=\"_blank\" rel=\"noreferrer noopener\">disheartening observation\u003C\u002Fa> from her training: many women detailing (what we now recognize as) \u003Ca href=\"https:\u002F\u002Fwww.mymenopausecentre.com\u002Fsymptom-checker\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">menopausal symptoms\u003C\u002Fa> were handed over to her with the label “WW patient” (as in whiny woman) along with dismissive condolences. Even today, responses such as “It’s all in your head” or “Why the drama, get over it!” remain distressingly typical.\u003C\u002Fp>\n\n\n\n\u003Cp>The doctor also shared that it’s not uncommon for women to be taking 7-8-10 different medications for various symptoms by the time they reach her. These women recognize that something is wrong, seeking help from one doctor to another. However, healthcare professionals often fail to recognize (peri)menopause as the root cause. Instead, they either dismiss the issue or prescribe separate treatments for individual symptoms.\u003C\u002Fp>\n\n\n\n\u003Cp>This is worrisome for two reasons: these women fail to receive crucially important info on how to preserve their physical and mental health, strength, bone density, and muscle mass while taking a handful of unnecessary drugs day after day. And meanwhile, their overall quality of life doesn’t improve.\u003C\u002Fp>\n\n\n\n\u003Cp>(Peri)menopause symptoms can be confusing: from heart palpitations to anxiety, from sleep troubles to weight gain, from tinnitus to brain fog, from burning mouth to muscle pains, bloating, hair loss and fatigue – seemingly unrelated, very varied. But they are also well documented and should be considered when a woman in the right age cohort (meaning: over 35) starts listing them. Or so you would think.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">70% have serious symptoms, 10% receive treatment info\u003C\u002Fh2>\n\n\n\n\u003Cp>While 70% of women report that (peri)menopause symptoms negatively affect their quality of life, only 10% get sufficient information about treatment options – these shocking figures come from \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=uEZpg0n7jcY\" target=\"_blank\">this interview\u003C\u002Fa>. Canadian Dr. Peter Attia talks about how misinterpretations of the results of the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FWomen%27s_Health_Initiative\" target=\"_blank\">Women’s Health Initiative (WHI)\u003C\u002Fa> resulted in demonizing hormone replacement therapies in the past few decades. \u003C\u002Fp>\n\n\n\n\u003Cp>Hormone replacement therapy faced a significant setback when results generated a widespread media hysteria reporting that HRT increased cancer risk by 25%. However, a closer examination reveals that the actual increase was from a very small risk to a slightly larger (but still very small) risk. In fact, HRT’s long-term protective effects against cardiovascular disease, osteoporosis, muscle loss, mental health issues, and weight management are well-documented and compelling. Yet, the misinterpretation of the WHI study tarnished HRT’s reputation for decades.\u003C\u002Fp>\n\n\n\n\u003Cp>For many women, HRT \u003Ca href=\"https:\u002F\u002Fwww.mayoclinic.org\u002Fdiseases-conditions\u002Fmenopause\u002Fin-depth\u002Fhormone-therapy\u002Fart-20046372\" target=\"_blank\" rel=\"noreferrer noopener\">can be an effective\u003C\u002Fa> way to \u003Ca href=\"https:\u002F\u002Fwww.menopause.org\u002Ffor-women\u002Fexpert-answers-to-frequently-asked-questions-about-menopause\" target=\"_blank\" rel=\"noreferrer noopener\">manage menopausal symptoms\u003C\u002Fa> and improve quality of life. It can help with immediate symptoms, and it can also offer decade-long protection against osteoporosis and cardiovascular disease. But we just don’t know about it.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Digital health to the rescue?\u003C\u002Fh2>\n\n\n\n\u003Cp>There are signs that the digital health sector is starting to recognize the significant potential for innovation in menopause care. One indication of this is the emergence of calls for research, \u003Ca href=\"https:\u002F\u002Fwww.frontiersin.org\u002Fresearch-topics\u002F57739\u002Fusing-digital-health-technologies-to-manage-symptoms-of-menopause\" target=\"_blank\" rel=\"noreferrer noopener\">such as this one\u003C\u002Fa>:\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png\" alt=\"TMF, medical student, AI, doctor, data, computer\" class=\"wp-image-50547\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F04\u002Ftmf_article_357.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>“The goal of this Research Topic is to bring together a collection of papers that individually and collectively used digital technologies to shed light on the symptom experience during the menopause transition. In so doing, these insights will identify novel strategies for both clinicians and researchers to use in improving the clinical tools and advancing the science needed for enhancing the management of menopause symptoms.”\u003C\u002Fp>\n\n\n\n\u003Cp>This call for research highlights the growing recognition that digital technologies can be leveraged to:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Improve symptom tracking and monitoring: digital tools can empower women to track their symptoms more accurately and consistently, providing valuable data for clinicians to inform treatment decisions.\u003C\u002Fli>\n\n\n\n\u003Cli>Enhance self-care: mobile apps and other digital resources can provide women with personalized guidance and support for managing their symptoms, promoting self-efficacy and reducing the burden on healthcare systems.\u003C\u002Fli>\n\n\n\n\u003Cli>Advance clinical research: digital technologies can facilitate the collection of large-scale, real-world data on menopause symptoms, enabling researchers to identify new patterns and trends, and develop more effective treatments.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>The global menopause market hit $15.4 billion in 2021 and is projected to reach $24.4 billion by 2030, according to \u003Ca href=\"https:\u002F\u002Fwww.grandviewresearch.com\u002Findustry-analysis\u002Fmenopause-market\" target=\"_blank\" rel=\"noreferrer noopener\">data\u003C\u002Fa> from Grand View Research – \u003Ca href=\"https:\u002F\u002Fwww.fiercehealthcare.com\u002Fhealth-tech\u002Fmenopause-care-market-remains-largely-untapped-heres-why-investors-and-startups-should\" target=\"_blank\" rel=\"noreferrer noopener\">Fierce Healthcare reported\u003C\u002Fa>. According to findings from a \u003Ca href=\"https:\u002F\u002Fwww.aarp.org\u002Fhealth\u002Fconditions-treatments\u002Finfo-2018\u002Fmenopause-symptoms-doctors-relief-treatment.html\" target=\"_blank\" rel=\"noreferrer noopener\">survey\u003C\u002Fa>, of women who seek medical attention 75% are left untreated.\u003C\u002Fp>\n\n\n\n\u003Cp>This is a vast market potential. Venture capital firm SJF Ventures identified 50 startups working in this area, \u003Ca href=\"https:\u002F\u002Fsjfventures.com\u002Fsjf-ventures-market-analysis-outlines-startups-disrupting-menopause-care-and-opportunities-for-investors\u002F#_ftn3\" target=\"_blank\" rel=\"noreferrer noopener\">delivering solutions in five sectors\u003C\u002Fa>, many of which (but not all) list scientific publications and clinical trials on their sites. These categories are\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Biopharma: biopharmaceutical and therapeutic solutions to ovarian health and menopause symptoms.\u003C\u002Fli>\n\n\n\n\u003Cli>Consumer Goods: health supplements, personal care, and sexual wellness products.\u003C\u002Fli>\n\n\n\n\u003Cli>Digital Technology: platforms for menopause management, including symptom tracking, educational resources, and social networks. \u003C\u002Fli>\n\n\n\n\u003Cli>Medical Devices: devices or wearables that alleviate menopause symptoms such as hot flashes and vulvovaginal atrophy. \u003C\u002Fli>\n\n\n\n\u003Cli>Virtual and Hybrid Care: clinical care, including consultations and medications, for menopause symptoms.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">There are many apps for that\u003C\u002Fh2>\n\n\n\n\u003Cp>If a woman reaches the point where she suspects she might be experiencing menopause symptoms, there are numerous apps to aid her journey. I’ve downloaded and tested several myself in recent weeks – including \u003Ca href=\"https:\u002F\u002Fwww.balance-menopause.com\u002Fbalance-app\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Balance\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fheyperry.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Perry\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fhellocaria.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Caria\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.hopkinsmedicine.org\u002Fnews\u002Farticles\u002F2020\u002F06\u002Fgynecologist-develops-menopause-guide-for-physicians\" target=\"_blank\" rel=\"noreferrer noopener\">Menopause\u003C\u002Fa>. Here’s what I’ve learned:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>You can save considerable time by getting detailed info from the app compared to starting research from scratch.\u003C\u002Fli>\n\n\n\n\u003Cli>Most apps I tested did an excellent job collecting menopause symptoms.\u003C\u002Fli>\n\n\n\n\u003Cli>Most go beyond basic symptom recording. They promote a holistic approach, offering advice, programs, and information about how to adjust lifestyle, sleep, nutrition, and exercise to offset symptoms and the long-term negative effects of hormonal changes.\u003C\u002Fli>\n\n\n\n\u003Cli>Several apps feature reviews where users evaluate the effectiveness of various treatment options (HRT, herbal therapies, lifestyle changes) determining whether they helped significantly, slightly, or not at all. This is immensely helpful for learning about various treatment options and making informed decisions.\u003C\u002Fli>\n\n\n\n\u003Cli>I tried free apps, and all of these come with in-app purchases. Understandable, they need to make money somehow. But they are also quite annoying with their aggressive pushiness, and tons of locked premium features. On the other hand, they are typically not expensive, and if you haven’t learned a Ph.D. worth of info by the time you get them and live in their service area – US mostly – using the full-access versions must be much better. \u003C\u002Fli>\n\n\n\n\u003Cli>The Menopause app from Johns Hopkins is an outlier, which was specifically developed for healthcare providers. Although I am not the target audience, I found its matter-of-fact tone, lack of sales push, and depth of information comforting.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>Overall, these apps are great resources for women at this particular stage of life. It’s crucial, however, to raise awareness that they exist, so others find them before they have to spend months researching the topic and visiting dozens of doctors looking for the non-existent illness making them feel off.\u003C\u002Fp>\n",{"rendered":207,"protected":20},"\u003Cp>While 70% of women in (peri)menopause have symptoms, only 10% get sufficient info about treatments – this is a potential goldmine for digital health\u003C\u002Fp>\n",54889,{"_acf_changed":20,"footnotes":27},[211,212],7079,4879,[214,215],7565,7907,[217,218,219],949,950,951,[],[222,223,224,225,226,227,228,229],1579,1617,1737,1871,2079,2199,1559,1571,[231,14,65,66,67,68,69,232,233,234,235,236,237,238],"post-54887","category-tmf","category-lifestyle-medicine","tag-female-health","tag-menopause-tech","project_category-educators","project_category-medical-professionals","project_category-patients",{"id":208,"alt_text":240,"caption":27,"description":27,"media_type":90,"media_details":241,"post":124,"source_url":279},"menopause, female health, women, app",{"width":242,"height":243,"file":244,"filesize":245,"sizes":246,"image_meta":277},6667,3750,"2024\u002F02\u002Ftmf_article_402.png",1206102,{"medium":247,"large":253,"thumbnail":259,"medium_large":264,"1536x1536":265,"2048x2048":271},{"file":248,"width":249,"height":250,"mime-type":100,"filesize":251,"source_url":252},"tmf_article_402-370x208.png",370,208,31474,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402-370x208.png",{"file":254,"width":255,"height":256,"mime-type":100,"filesize":257,"source_url":258},"tmf_article_402-768x432.png",768,432,85077,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402-768x432.png",{"file":260,"width":261,"height":261,"mime-type":100,"filesize":262,"source_url":263},"tmf_article_402-150x150.png",150,14845,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402-150x150.png",{"file":254,"width":255,"height":256,"mime-type":100,"filesize":257,"source_url":258},{"file":266,"width":267,"height":268,"mime-type":100,"filesize":269,"source_url":270},"tmf_article_402-1536x864.png",1536,864,224658,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402-1536x864.png",{"file":272,"width":273,"height":274,"mime-type":100,"filesize":275,"source_url":276},"tmf_article_402-2048x1152.png",2048,1152,346448,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402-2048x1152.png",{"aperture":118,"credit":27,"camera":27,"caption":27,"created_timestamp":118,"copyright":27,"focal_length":118,"iso":118,"shutter_speed":118,"title":27,"orientation":118,"keywords":278},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_402.png",{"cta_type":281,"cta_color":27,"related_books":282,"related_posts_footer":285,"related_posts":20,"subtitle":27,"key_takeaways":289},"subscribe",[283,127,284],30419,47427,[286,287,288],54593,54743,54485,[290,292,294],{"title":291},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">An overwhelming majority of women enter perimenopause with little to no knowledge about symptoms or treatment options, underscoring a critical gap in women’s healthcare education and support\u003C\u002Fspan>\u003C\u002Fp>\n",{"title":293},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">Despite the profound impact of menopause on health and the economy, with an estimated annual global cost of $150 billion, menopause research and solutions are dramatically underfunded and overlooked\u003C\u002Fspan>\u003C\u002Fp>\n",{"title":295},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">Digital health innovations offer promising new avenues for managing menopause symptoms, providing personalized care and filling the void left by traditional healthcare through symptom tracking, telemedicine, and educational resources\u003C\u002Fspan>\u003C\u002Fp>\n",{"yoast_wpseo_title":203,"yoast_wpseo_metadesc":297,"yoast_wpseo_canonical":201},"While 70% of women in (peri)menopause have symptoms, only 10% get sufficient info about treatments - this is a potential goldmine for digital health",{"self":299,"collection":304,"about":306,"author":308,"replies":310,"version-history":313,"predecessor-version":317,"wp:featuredmedia":321,"wp:attachment":324,"wp:term":327,"curies":338},[300],{"href":301,"targetHints":302},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54887",{"allow":303},[145],[305],{"href":148},[307],{"href":151},[309],{"embeddable":26,"href":154},[311],{"embeddable":26,"href":312},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=54887",[314],{"count":315,"href":316},17,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54887\u002Frevisions",[318],{"id":319,"href":320},54943,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54887\u002Frevisions\u002F54943",[322],{"embeddable":26,"href":323},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F54889",[325],{"href":326},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=54887",[328,330,332,334,336],{"taxonomy":174,"embeddable":26,"href":329},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=54887",{"taxonomy":177,"embeddable":26,"href":331},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=54887",{"taxonomy":180,"embeddable":26,"href":333},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=54887",{"taxonomy":183,"embeddable":26,"href":335},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=54887",{"taxonomy":186,"embeddable":26,"href":337},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=54887",[339],{"name":190,"href":191,"templated":26},[341],{"id":129,"date":342,"date_gmt":343,"guid":344,"modified":346,"modified_gmt":347,"slug":348,"status":13,"type":349,"link":350,"title":351,"content":353,"excerpt":355,"author":357,"featured_media":358,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":359,"class_list":361,"better_featured_image":364,"acf":382,"yoast_meta":406,"_links":408},"2019-09-06T21:56:27","2019-09-06T19:56:27",{"rendered":345},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=24759","2023-03-12T18:06:35","2023-03-12T17:06:35","the-technological-future-of-medical-specialties","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fthe-technological-future-of-medical-specialties\u002F",{"rendered":352},"The Technological Future of Medical Specialties",{"rendered":354,"protected":20},"\n\u003Cp>In this e-book we specify in detail how the appearance of artificial intelligence, sensors, wearables, VR\u002FAR or robots affect each medical specialty in order to be able to discern what skills physicians will need in the future. We aim to show how physicians of the various professions can successfully prepare for the sweeping changes coming with the waves of technology. \u003C\u002Fp>\n",{"rendered":356,"protected":20},"\u003Cp>In this e-book we specify in detail how the appearance of artificial intelligence, sensors, wearables, VR\u002FAR or robots affect each medical specialty in order to […]\u003C\u002Fp>\n",10,49971,[360],2015,[362,349,363,66,68,69],"post-24759","type-book",{"id":358,"alt_text":27,"caption":27,"description":27,"media_type":90,"media_details":365,"post":129,"source_url":381},{"width":366,"height":367,"file":368,"filesize":369,"sizes":370,"image_meta":380},320,414,"2019\u002F09\u002Ffuture-of-medical-specialties.png",24785,{"medium":371,"thumbnail":376},{"file":372,"width":373,"height":99,"mime-type":100,"filesize":374,"source_url":375},"future-of-medical-specialties-320x208.png","320","52681","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties-320x208.png",{"file":377,"width":109,"height":109,"mime-type":100,"filesize":378,"source_url":379},"future-of-medical-specialties-150x150.png","26567","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties-150x150.png",{"aperture":118,"credit":27,"camera":27,"caption":27,"created_timestamp":118,"copyright":27,"focal_length":118,"iso":118,"shutter_speed":118,"title":27,"orientation":118},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties.png",{"leanpub_url":383,"buy_button_text":384,"preview":385},"https:\u002F\u002Fleanpub.com\u002Ffuture-of-medical-specialties","Get it on Leanpub",[386,388,390,392,394,396,398,400,402,404],{"image":387},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-01.png",{"image":389},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-02.png",{"image":391},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-03.png",{"image":393},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-04.png",{"image":395},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-05.png",{"image":397},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-06.png",{"image":399},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-07.png",{"image":401},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-08.png",{"image":403},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-09.png",{"image":405},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-10.png",{"yoast_wpseo_title":407,"yoast_wpseo_metadesc":27,"yoast_wpseo_canonical":350},"The Technological Future of Medical Specialties - The Medical Futurist",{"self":409,"collection":414,"about":417,"author":420,"replies":423,"wp:featuredmedia":426,"wp:attachment":429,"wp:term":432,"curies":435},[410],{"href":411,"targetHints":412},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F24759",{"allow":413},[145],[415],{"href":416},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[418],{"href":419},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[421],{"embeddable":26,"href":422},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F10",[424],{"embeddable":26,"href":425},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=24759",[427],{"embeddable":26,"href":428},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49971",[430],{"href":431},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=24759",[433],{"taxonomy":186,"embeddable":26,"href":434},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=24759",[436],{"name":190,"href":191,"templated":26},1789237860726]