[{"data":1,"prerenderedAt":414},["ShallowReactive",2],{"slug-how-an-a-i-based-skin-checking-app-can-work-with-a-national-healthcare-system":3},{"post":4,"relatedPosts":191,"relatedBooks":330},{"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":39,"project_category":50,"contact_email_category":57,"yst_prominent_words":58,"class_list":62,"better_featured_image":93,"acf":127,"yoast_meta":137,"_links":139},47129,"2022-09-08T10:00:00","2022-09-08T08:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=47129&_wpnonce=8c120cc6be&status=auto-draft&type=post","2022-09-14T20:53:25","2022-09-14T18:53:25","how-an-a-i-based-skin-checking-app-can-work-with-a-national-healthcare-system","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fhow-an-a-i-based-skin-checking-app-can-work-with-a-national-healthcare-system",{"rendered":17},"How An A.I.-Based Skin Checking App Can Work With A National Healthcare System",{"rendered":19,"protected":20},"\n\u003Cp>You might be already familiar with \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fskin-checking-algorithms\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">skin checking apps\u003C\u002Fa>, we too have discussed them quite extensively recently. Skin checking applications allow users to take pictures of their suspicious skin lesions, upload these pictures to a server, the images are first evaluated by an A.I. algorithm and the results will be later validated by a dermatologist. \u003C\u002Fp>\n\n\n\n\u003Cp>However, this time there is something new under the sun: \u003Ca href=\"https:\u002F\u002Fwww.aip.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">AIP Labs\u003C\u002Fa> and Semmelweis University (Hungary’s leading medical university) developed a skin checking application that offers several features we have not seen before. It was launched to work integrated with the national healthcare system and offer full-scope dermatology services including diagnostics, treatment plans and cloud-based drug subscriptions. According to currently available data, processing speeds have improved by 5-10 times compared to the traditional care model. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image is-style-default\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh5.googleusercontent.com\u002FovV5U5DcyLTmFWz9TdopWZoQORdizvra3ewfZhBGs6Ek79rxdgxpsb8N8jcijqo80Cfdeo_OXotkcGkyBhjPesfiWBAxRnEinEt01i0YXoHE8A5Z-cKwh5zRvq3_oMYxMuI37obHrUH0NQT-fKQ6Dig\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>In this analysis, \u003Ca href=\"https:\u002F\u002Fwww.medicalfuturist.com\u002Fskin-checking-algorithms\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">we called these apps an emerging trend\u003C\u002Fa>, and still stand by this statement. If you are looking for a signature digital health solution, these are great examples, as they:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>address an existing demand\u003C\u002Fli>\u003Cli>rely on already existing infrastructure from the patients’ side (eg: their mobile phones)\u003C\u002Fli>\u003Cli>provide easy and cheap access to patients who otherwise might have difficulties with scheduling dermatology appointments for any reason, like physical distance, insurance problems, anxiety and so on\u003C\u002Fli>\u003Cli>allow fast and reliable evaluation of skin lesions, cutting down waiting times\u003C\u002Fli>\u003Cli>eliminate unnecessary medical visits, saving time for both patient and clinician\u003C\u002Fli>\u003Cli>assist dermatologists, who can check significantly more cases in a given amount of time\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cp>We could even conclude that if such a system provides follow-up and access to doctors and treatments should the need arise, these are close to the optimal setup – they filter out non-existing cases and let dermatologists focus on the real issues. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Unique model: launching a skin checking app integrated with the national healthcare system\u003C\u002Fh2>\n\n\n\n\u003Cp>While these apps are not exactly new, this is an exciting collaboration between the healthcare system, the country’s leading medical university and the developer of the A.I.-based solution, called \u003Ca href=\"https:\u002F\u002Fsemmelweis.aip.ai\u002Fen\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">AIP Derm\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>The uniqueness of the model is that it offers some features we have not seen before, like:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>Free access to all patients with social security during the test period\u003C\u002Fli>\u003Cli>Diagnosing not just suspicious skin lesions for cancer risk, but hundreds of dermatology conditions\u003C\u002Fli>\u003Cli>Offering drug subscriptions through the country’s electronic medical system\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cp>In other words, Hungarian patients with any skin problem could turn to the app, upload their pictures, answer some questions, and receive a diagnosis in just a few days. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The model has four end scenarios\u003C\u002Fh2>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>No treatment is necessary\u003C\u002Fli>\u003Cli>The dermatologist suggests using over-the-counter medication \u003C\u002Fli>\u003Cli>The dermatologist suggests using subscription-only medication by providing an e-subscription via the central online medical system, allowing the patient to pick up the drug at the nearest pharmacy\u003C\u002Fli>\u003Cli>Suggests a personal appointment for the treatment\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Covering some 95% of skin diseases\u003C\u002Fh2>\n\n\n\n\u003Cp>AIP Derm currently detects 700 pathologies, covering some 95% of skin diseases. The submitted images and the diagnosis created by the A.I. are always reviewed by a doctor. Once an image comes in, the system pre-evaluates it, tells the dermatologist team which pathologies it believes are likely to be involved, and then sorts them by chronological order or severity. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image is-style-default\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh4.googleusercontent.com\u002FbXW_2IYxmRP_E8hBZ0_iPrXPcVHWxqVeUXlTMAG4aAEyb9TnelARd2Y69Ay9NBq8CGsJ0GgUsiToMeKBtBwH1ZNDZ0giYwlImjac7HMYFtTe-Ms8X2Hg2Ts-5a9pkg-HgpZHWC-sTL0dFJh108TgERM\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>According to data collected in the first few months, doctors choose one of the first three options 90% of the time. Doctors see the cases triaged based on urgency. The A.I. algorithm offers 3 possible diagnoses for dermoscopic images and 5 for macroscopic images. If a dermatologist can’t address a case within 20 seconds, they can ask the patient to submit additional photos or suggest an in-person consultation. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Over 80% of skin cancer cases were detected early\u003C\u002Fh2>\n\n\n\n\u003Cp>In total, 18.114 cases were submitted by patients during the test period between March and June of 2022. The three most common skin conditions were Common moles, Seborrheic Keratosis and Contact Dermatitis.\u003C\u002Fp>\n\n\n\n\u003Cp>Just over six hundred cases of skin cancer were diagnosed during this period. Some were surprisingly advanced. The largest tumour detected was late-stage cancer, over 3 cm wide. But in general, most cases (over 80%) were in the early stages. This shows that A.I. is a very powerful accelerator for preventive healthcare. The detected cases were diagnosed under five categories: basal-cell-carcinoma(57%), melanoma (29%), squamous-cell-carcinoma (5%), squamous-cell-carcinoma-in-situ (4%) and invasive-cutaneous-squamous-cell-carcinoma (3%).\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Processing speeds have improved by 5-10 times\u003C\u002Fh2>\n\n\n\n\u003Cp>In the pilot, 10 doctors of the Semmelweis University Clinic of Dermatology, Venereology and Dermatooncology worked to evaluate the uploaded cases, they were able to go through 40-80 images per hour. These clinicians provided the treatment suggestions, issued the cloud-based drug subscriptions and suggested in-person consultation if necessary. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image is-style-default\">\u003Cimg decoding=\"async\" src=\"https:\u002F\u002Flh6.googleusercontent.com\u002FfpaghKJZ0VPxcsEuKAUhKch4CIVFf3YlJBUTIYHGZIRUX0xyekcAwFnWIU6STX_XyLWKB0RnSibuEoskQ6OihBQu_h-Q5HsdLlrhA8DlJI0QliXFty0EdAqUFbFOOQqpNCfWl2HnmOOUScfzvcJdKFE0vviruz1vwfd5l3nN33jMz3ZB3_Bx0azhPQ\" alt=\"\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Unlike other skin-checking apps, this model was designed to work as a remote-only service – as opposed to being a telehealth solution with online consultation and follow-up. The reason for going this route was to examine whether it allows significant capacity increase. If doctors need to spend time with online consultations, this benefit is mostly lost. Participating clinicians’ reported that processing speeds have improved by 5-10 times compared to the traditional care model.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">A variety of deep-learning models\u003C\u002Fh2>\n\n\n\n\u003Cp>AIP Derm has a variety of deep-learning algorithms that form both the visual engine and the Q&A engine, whose design and performance were optimised from the Hungarian pilot and other European initiatives. It is built on a convolutional neural network, and it’s currently being replaced by A.I. transformator technology. Validation has been done through the Semmelweis University Dermatology Clinic and private dermatologists over a period of 18 months. \u003C\u002Fp>\n\n\n\n\u003Cp>The model was trained on 2 million images, developed entirely on in-house infrastructure. The database is made up of skin images that were contributed by clinics and hospitals globally.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">How is the algorithm trained? \u003C\u002Fh2>\n\n\n\n\u003Cp>It is a very complex process with individually sophisticated components that require careful clinical and evidence-based feedback to verify certain development hypotheses. In simple terms, developers are constantly collecting data as the platform is being used, which is the “raw” image and profile\u002FQ&A data collected with each case, which allows them to build the internal training databases used for algorithm development, while also validating its performance on real-world data and use.\u003C\u002Fp>\n\n\n\n\u003Cp>AIP uses several techniques when training new deep-learning models. To address class imbalances (when more examples exist for one class than the other) in the training data, additional weights are applied to mistakes made on under-represented classes, which encourages the model to better detect cases with low prevalence in the dataset. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Additional paid services after the test period\u003C\u002Fh2>\n\n\n\n\u003Cp>The business model is geared towards addressing one of the fundamental pain points in healthcare: too many patients and too few clinicians. AIP will serve as a one-stop shop health care delivery system over the next several years in the Hungarian market. \u003C\u002Fp>\n\n\n\n\u003Cp>Accelerated and at-home digital diagnostics will be available in the last quarter of the year nationwide as an additional service on top of social security benefits for a fee – at a fraction of the market price. Patients will continue to receive a diagnosis, with an outpatient form, and a digital prescription that can be redeemed at any pharmacy.\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>Doctors’ processing speeds have improved by 5-10 times, the app covers 95% of skin diseases and patients also get drug prescriptions via the cloud. \u003C\u002Fp>\n",6,34783,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32,33,34,35,36,37,38],7079,504,798,491,521,499,800,494,[40,41,42,43,44,45,46,47,48,49],727,134,144,7203,207,7225,275,7607,7623,1012,[51,52,53,54,55,56],948,949,950,951,952,953,[],[59,60,61],2465,2519,1707,[63,14,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92],"post-47129","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","category-artificial-intelligence","category-digital-health-research","category-empowered-patients","category-future-medicine","category-healthcare-design","category-healthcare-policy","category-telemedicine","tag-dermatology","tag-ai","tag-artificial-intelligence","tag-skin-cancer","tag-digital-health","tag-skin-checker","tag-healthcare","tag-skin-checking-app","tag-digital-health-app","tag-skin","project_category-developers","project_category-educators","project_category-medical-professionals","project_category-patients","project_category-policy-makers","project_category-researchers",{"id":24,"alt_text":94,"caption":95,"description":27,"media_type":96,"media_details":97,"post":125,"source_url":126},"Emerging Trend Alert – Skin Checking Algorithms","Skin Checking Algorithms","image",{"width":98,"height":99,"file":100,"sizes":101,"image_meta":123},1920,1080,"2021\u002F06\u002Ftmf_article_274-01.png",{"medium":102,"large":108,"thumbnail":113,"medium_large":117,"1536x1536":118},{"file":103,"width":104,"height":105,"mime-type":106,"source_url":107},"tmf_article_274-01-370x208.png","370","208","image\u002Fpng","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01-370x208.png",{"file":109,"width":110,"height":111,"mime-type":106,"source_url":112},"tmf_article_274-01-768x432.png","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01-768x432.png",{"file":114,"width":115,"height":115,"mime-type":106,"source_url":116},"tmf_article_274-01-150x150.png","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01-150x150.png",{"file":109,"width":110,"height":111,"mime-type":106,"source_url":112},{"file":119,"width":120,"height":121,"mime-type":106,"source_url":122},"tmf_article_274-01-1536x864.png","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01-1536x864.png",{"aperture":124,"credit":27,"camera":27,"caption":27,"created_timestamp":124,"copyright":27,"focal_length":124,"iso":124,"shutter_speed":124,"title":27,"orientation":124},"0",34743,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F06\u002Ftmf_article_274-01.png",{"cta_type":128,"cta_color":27,"related_books":129,"related_posts_footer":133,"related_posts":20,"subtitle":27},"subscribe",[130,131,132],24765,24762,37033,[134,135,136],47089,16269,44579,{"yoast_wpseo_title":17,"yoast_wpseo_metadesc":138,"yoast_wpseo_canonical":15},"Doctors' processing speeds have improved by 5-10 times, and patients also get drug prescriptions via the cloud. An exciting model to use skin checking apps.",{"self":140,"collection":146,"about":149,"author":152,"replies":155,"version-history":158,"predecessor-version":161,"wp:featuredmedia":165,"wp:attachment":168,"wp:term":171,"curies":187},[141],{"href":142,"targetHints":143},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47129",{"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=47129",[159],{"count":23,"href":160},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47129\u002Frevisions",[162],{"id":163,"href":164},47291,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47129\u002Frevisions\u002F47291",[166],{"embeddable":26,"href":167},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F34783",[169],{"href":170},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=47129",[172,175,178,181,184],{"taxonomy":173,"embeddable":26,"href":174},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=47129",{"taxonomy":176,"embeddable":26,"href":177},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=47129",{"taxonomy":179,"embeddable":26,"href":180},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=47129",{"taxonomy":182,"embeddable":26,"href":183},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=47129",{"taxonomy":185,"embeddable":26,"href":186},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=47129",[188],{"name":189,"href":190,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[192],{"id":136,"date":193,"date_gmt":194,"guid":195,"modified":197,"modified_gmt":198,"slug":199,"status":13,"type":14,"link":200,"title":201,"content":203,"excerpt":205,"author":23,"featured_media":207,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":208,"categories":209,"tags":211,"project_category":217,"contact_email_category":218,"yst_prominent_words":219,"class_list":227,"better_featured_image":235,"acf":278,"yoast_meta":286,"_links":288},"2022-05-12T10:05:00","2022-05-12T08:05:00",{"rendered":196},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=44579&_wpnonce=4eb16b3f6a&status=auto-draft&type=post","2022-05-12T10:01:58","2022-05-12T08:01:58","underfunding-research-of-female-health-leaves-huge-amounts-of-money-on-the-table","https:\u002F\u002Fmedicalfuturist.com\u002Funderfunding-research-of-female-health-leaves-huge-amounts-of-money-on-the-table",{"rendered":202},"Underfunding Research Of Female Health Leaves Huge Amounts Of Money On The Table",{"rendered":204,"protected":20},"\n\u003Cp>“Did you know that at least one-third of women have lower back pain before their periods every month, and yet, nobody seems to fully understand why?” – asked a Medical Futurist team member a little while ago. The question led to a discussion about the differences in research, funding and understanding of male-only and female-only health issues, and consequently, to this article.\u003C\u002Fp>\n\n\n\n\u003Cp>It is a well-known fact that some diseases or conditions dominantly affect one gender or the other. There are the trivial ones, like prostate cancer or ovarian, cervical, uterine cancers. But there is a long list of diseases and conditions that have a significantly higher prevalence among one of the sexes, like liver cancer or tuberculosis occurring more often in the male population, and autoimmune diseases or multiple sclerosis among the females.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Why does a symptom affecting 19% of men get five times more funding than a symptom affecting 90% of women?  \u003C\u002Fh3>\n\n\n\n\u003Cp>The interesting thing is, that figures suggest that although roughly half the population is female pretty much all across the globe, research on female-dominant diseases is underfunded, while male-dominant ones are overfunded. \u003C\u002Fp>\n\n\n\n\u003Cp>This is not something that is easily quantified, but \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.liebertpub.com\u002Fdoi\u002Fepub\u002F10.1089\u002Fjwh.2020.8682\" target=\"_blank\">this study tried to do this job\u003C\u002Fa>. It came to the conclusion that “the degree of funding disparity for the male-favored diseases (extent to which male-dominant diseases are overfunded and female-dominant diseases underfunded) is nearly twice as large as that for the female-favored diseases.”\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"650\" height=\"445\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F05\u002Fdifference-in-funding-male-and-female-health.jpg\" alt=\"\" class=\"wp-image-44583\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>One easy to grasp example: premenstrual syndromes, affecting 90% of women, get one-fifth of the funding of erectile dysfunctions, affecting 19% of men. But the list goes on and on. Endometriosis, Alzheimer’s, Crohn disease, rheumatoid arthritis and autoimmune conditions are just a few of the diseases that are affecting women significantly more and receive only a moderate amount of research funding.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Females were not included in clinical trials before 1993, not even in mice\u003C\u002Fh3>\n\n\n\n\u003Cp>Some of the reasons for the “gender gap” we see in health-research and its funding are historical. And we don’t even need to go back centuries, only a few decades to find some interesting things. \u003C\u002Fp>\n\n\n\n\u003Cp>The US Food And Drug Administration (FDA) excluded women “of child-bearing potential” \u003Ca href=\"https:\u002F\u002Fwww.fda.gov\u002Fscience-research\u002Fwomens-health-research\u002Fregulations-guidance-and-reports-related-womens-health\" target=\"_blank\" rel=\"noreferrer noopener\">from all clinical trials between 1977 and 1993\u003C\u002Fa>. This means that all these years all clinical trials were carried out exclusively on men. And not only in humans, but also in mice. \u003C\u002Fp>\n\n\n\n\u003Cp>The reasons were two folds. Regulators were worried about potential complications of foetal malformation, following the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.bbc.com\u002Fnews\u002Fmagazine-15536544\" target=\"_blank\">European withdrawal of the sedative Thalidomide\u003C\u002Fa>. This drug was used to suppress early pregnancy symptoms, and, as later was acknowledged, caused a vast number of birth deformities in the late 50’s. But this was not the only reason. Apparently, female hormonal cycles made things too complicated. The variability would mean more subjects were needed in clinical trials, thereby increasing costs. So including only male subjects in clinical trials was an economically justifiable solution. Or so it seemed. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">No wonder, women have 50-75% more side effects from drugs\u003C\u002Fh3>\n\n\n\n\u003Cp>The fact that women generally experience significantly more side effects from various drugs is not surprising after knowing how they were not included in clinical trials for quite a long time. But 1993 was a while ago, things surely must have changed since then – we might think.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-768x432.png\" alt=\"AI bias algorithm artificial intelligence people patients race population\" class=\"wp-image-41809\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F04\u002FAI-bias.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Apparently, things indeed have changed, but not so much. Some 80% of all drugs removed from the US market \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.gao.gov\u002Fproducts\u002Fgao-01-286r\" target=\"_blank\">between 1997 and 2000\u003C\u002Fa> were withdrawn because their side effects occurred mainly or exclusively in women. And the trend continued. Between 2004 and 2013, women suffered more than 2 million drug-related adverse events, compared with 1.3 million for men in the United States. \u003C\u002Fp>\n\n\n\n\u003Cp>Even in 2015, \u003Ca href=\"https:\u002F\u002Fwww.theguardian.com\u002Flifeandstyle\u002F2015\u002Fapr\u002F30\u002Ffda-clinical-trials-gender-gap-epa-nih-institute-of-medicine-cardiovascular-disease\" target=\"_blank\" rel=\"noreferrer noopener\">only about a third of participants in clinical trials for new treatments for cardiovascular disease were female\u003C\u002Fa>, despite cardiovascular diseases being the number one cause of death in American women. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">How about spending only a little more to have a ROI of 174,000 percent?\u003C\u002Fh3>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ffortune.com\u002F2022\u002F02\u002F11\u002Fwomen-health-medical-research-underfunding-equity-rand\u002F\" target=\"_blank\">As this article explains\u003C\u002Fa>, underfunding research about female health problems leaves a huge amount of money on the table. Sounds strange, right? After all, what we say is exactly that there should be more spending. But under-researched female health problems have incredible societal costs. Not only in the labour market, where conditions like rheumatoid arthritis, autoimmune diseases and similar ‘womanly’ problems take off years of the careers of millions. But also in other areas: paying for the extra years in elderly care or losing the capacities of females, who are the primary caretakers in most families. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.rand.org\u002Fblog\u002F2022\u002F02\u002Funderfunding-of-research-in-womens-health-issues-is.html\" target=\"_blank\">Researchers can provide shocking numbers\u003C\u002Fa> to back their claims about why societies should focus more on female health. \u003C\u002Fp>\n\n\n\n\u003Cp>For example, they examined what might happen if the budget for Alzheimer’s research into women specifically went from $288 million to $576 million. In these simulations, they conservatively assumed that this budgetary increase would deliver just 0.01 percent of health improvements for Alzheimer’s and coronary artery disease, and 0.1 percent for rheumatoid arthritis, over 30 years.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"433\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled-768x433.png\" alt=\"Women and digital health\" class=\"wp-image-23124\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled-768x433.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled-1536x866.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002F070_womens_health-scaled.png 1915w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>“Even these slivers of improvement produced a shockingly high return on investment. By doubling the NIH budget for research on coronary artery disease in women from its current $20 million, we could expect an ROI of 9,500 percent. \u003C\u002Fp>\n\n\n\n\u003Cp>Studies focused on rheumatoid arthritis in women receive just $6 million a year. Doubling that would deliver an ROI of 174,000 percent and add $10.5 billion to our economy over the 30-year timespan” – the study says. Well, that is one hell of a ROI for sure. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">So why don’t we spend on it if that is such a big business? \u003C\u002Fh3>\n\n\n\n\u003Cp>There is a huge amount of literature and debate about why exactly (and if at all) research targeting female health problems is underfunded in general. Some argue that the reason is quite simple: there are just too few female-targeted research initiatives, and instead of looking for discrimination, there should be more research projects submitted for funding.\u003C\u002Fp>\n\n\n\n\u003Cp>Others see the situation a little more nuanced and believe that it is the result of many, overlapping structural problems, like the underrepresentation of women in science in general and especially in leading positions, the hard-to-pin but existing difference in the prestige of male and female researchers, gender inequities among decision-makers allocating funds and so on.\u003C\u002Fp>\n\n\n\n\u003Cp>With all that said, these problems will surely not disappear by tomorrow, but we can expect that the development of healthcare and digital health tools will be part of the solution. Female health-related startups are definitely getting momentum – and funding – over the past decade, and the sheer amount of available health data coming from both genders will also contribute to a better understanding of the biological differences between how men and women react to drugs, treatments and ageing. \u003C\u002Fp>\n",{"rendered":206,"protected":20},"\u003Cp>Under-researched female health problems have incredible societal costs. Not only on the labour market, where conditions like rheumatoid arthritis, autoimmune diseases and similar ‘womanly’ problems take off years of the careers of millions. But also in other areas: paying for the extra years in elderly care or losing the capacities of females, who are the primary caretakers in most families. \u003C\u002Fp>\n",23121,{"_acf_changed":20,"footnotes":27},[31,35,37,210],516,[212,213,214,215,216],7569,7571,7565,7567,1240,[52,53,54,55,56],[],[220,221,222,223,224,225,226],1621,1871,1885,2201,2211,2731,3585,[228,14,64,65,66,67,68,69,73,75,229,230,231,232,233,234,88,89,90,91,92],"post-44579","category-medical-education","tag-gender-gap-in-healthcare","tag-men","tag-female-health","tag-under-reseached","tag-women",{"id":207,"alt_text":236,"caption":237,"description":238,"media_type":96,"media_details":239,"post":276,"source_url":277},"femtech","Source: www.miifotos.com","female health",{"width":240,"height":241,"file":242,"sizes":243,"image_meta":274},1910,1000,"2019\u002F02\u002FWomen-In-Tech.jpg",{"medium":244,"large":250,"thumbnail":255,"medium_large":259,"1536x1536":260,"thumbnail_old_150x150":265,"medium_old_370x208":266,"medium_large_old_768x402":267,"large_old_512x268":269},{"file":245,"width":246,"height":247,"mime-type":248,"source_url":249},"Women-In-Tech-370x208.jpg",370,208,"image\u002Fjpeg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech-370x208.jpg",{"file":251,"width":252,"height":253,"mime-type":248,"source_url":254},"Women-In-Tech-768x402.jpg",768,402,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech-768x402.jpg",{"file":256,"width":257,"height":257,"mime-type":248,"source_url":258},"Women-In-Tech-150x150.jpg",150,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech-150x150.jpg",{"file":251,"width":252,"height":253,"mime-type":248,"source_url":254},{"file":261,"width":262,"height":263,"mime-type":248,"source_url":264},"Women-In-Tech-1536x804.jpg",1536,804,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech-1536x804.jpg",{"file":256,"width":115,"height":115,"mime-type":248,"source_url":258},{"file":245,"width":104,"height":105,"mime-type":248,"source_url":249},{"file":251,"width":110,"height":268,"mime-type":248,"source_url":254},"402",{"file":270,"width":271,"height":272,"mime-type":248,"source_url":273},"Women-In-Tech-512x268.jpg","512","268","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech-512x268.jpg",{"aperture":124,"credit":27,"camera":27,"caption":27,"created_timestamp":124,"copyright":27,"focal_length":124,"iso":124,"shutter_speed":124,"title":27,"orientation":124,"keywords":275},[],23116,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F02\u002FWomen-In-Tech.jpg",{"cta_type":128,"cta_color":27,"subtitle":27,"related_books":279,"related_posts_footer":282,"related_posts":20},[280,281,132],24763,34151,[283,284,285],23673,41849,20686,{"yoast_wpseo_title":202,"yoast_wpseo_metadesc":287,"yoast_wpseo_canonical":200},"Under-researched female health problems have incredible societal costs. Not only on the labour market, but also in other areas. ",{"self":289,"collection":294,"about":296,"author":298,"replies":300,"version-history":303,"predecessor-version":307,"wp:featuredmedia":311,"wp:attachment":314,"wp:term":317,"curies":328},[290],{"href":291,"targetHints":292},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F44579",{"allow":293},[145],[295],{"href":148},[297],{"href":151},[299],{"embeddable":26,"href":154},[301],{"embeddable":26,"href":302},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=44579",[304],{"count":305,"href":306},12,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F44579\u002Frevisions",[308],{"id":309,"href":310},45227,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F44579\u002Frevisions\u002F45227",[312],{"embeddable":26,"href":313},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F23121",[315],{"href":316},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=44579",[318,320,322,324,326],{"taxonomy":173,"embeddable":26,"href":319},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=44579",{"taxonomy":176,"embeddable":26,"href":321},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=44579",{"taxonomy":179,"embeddable":26,"href":323},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=44579",{"taxonomy":182,"embeddable":26,"href":325},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=44579",{"taxonomy":185,"embeddable":26,"href":327},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=44579",[329],{"name":189,"href":190,"templated":26},[331],{"id":132,"date":332,"date_gmt":333,"guid":334,"modified":336,"modified_gmt":337,"slug":338,"status":13,"type":339,"link":340,"title":341,"content":343,"excerpt":345,"author":23,"featured_media":347,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":348,"class_list":350,"better_featured_image":353,"acf":371,"yoast_meta":383,"_links":386},"2021-12-02T11:04:38","2021-12-02T10:04:38",{"rendered":335},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=37033","2025-05-29T13:51:30","2025-05-29T11:51:30","hype-cycle-of-the-top-50-emerging-digital-health-trends","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fhype-cycle-of-the-top-50-emerging-digital-health-trends\u002F",{"rendered":342},"The Technology Adoption Curve Of The Top 50 Emerging Digital Health Trends",{"rendered":344,"protected":20},"\n\u003Cp>This is the first time we publish The Medical Futurist’s Technology Adoption Curve, showing 50 of the most promising digital health technologies the way we, at The Medical Futurist, see them today. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003C\u002Fp>\n",{"rendered":346,"protected":20},"\u003Cp>This is the first time we publish The Medical Futurist’s Technology Adoption Curve, showing 50 of the most promising digital health technologies the way we, […]\u003C\u002Fp>\n",49955,[349],1723,[351,339,352,65,67,68],"post-37033","type-book",{"id":347,"alt_text":27,"caption":27,"description":27,"media_type":96,"media_details":354,"post":132,"source_url":370},{"width":355,"height":356,"file":357,"filesize":358,"sizes":359,"image_meta":368},320,414,"2021\u002F12\u002Fhype-cycle.png",79823,{"medium":360,"thumbnail":364},{"file":361,"width":355,"height":247,"mime-type":106,"filesize":362,"source_url":363},"hype-cycle-320x208.png",35531,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F12\u002Fhype-cycle-320x208.png",{"file":365,"width":257,"height":257,"mime-type":106,"filesize":366,"source_url":367},"hype-cycle-150x150.png",20118,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F12\u002Fhype-cycle-150x150.png",{"aperture":124,"credit":27,"camera":27,"caption":27,"created_timestamp":124,"copyright":27,"focal_length":124,"iso":124,"shutter_speed":124,"title":27,"orientation":124,"keywords":369},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F12\u002Fhype-cycle.png",{"buy_button_text":372,"leanpub_url":373,"preview":374},"Buy 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In this book, we analyze the Top 50 Digital Health Trends.",{"self":387,"collection":392,"about":395,"author":398,"replies":400,"wp:featuredmedia":403,"wp:attachment":406,"wp:term":409,"curies":412},[388],{"href":389,"targetHints":390},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F37033",{"allow":391},[145],[393],{"href":394},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[396],{"href":397},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[399],{"embeddable":26,"href":154},[401],{"embeddable":26,"href":402},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=37033",[404],{"embeddable":26,"href":405},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49955",[407],{"href":408},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=37033",[410],{"taxonomy":185,"embeddable":26,"href":411},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=37033",[413],{"name":189,"href":190,"templated":26},1789727348873]