[{"data":1,"prerenderedAt":451},["ShallowReactive",2],{"slug-synthetic-data-in-healthcare-will-smarter-data-bring-the-a-i-revolution-in-healthcare":3},{"post":4,"relatedPosts":183,"relatedBooks":354},{"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":34,"project_category":42,"contact_email_category":48,"yst_prominent_words":49,"class_list":63,"better_featured_image":85,"acf":118,"yoast_meta":127,"_links":130},37443,"2021-12-09T11:00:00","2021-12-09T10:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=37443&_wpnonce=7d4978e4fd&status=auto-draft&type=post","2021-12-13T09:51:47","2021-12-13T08:51:47","synthetic-data-in-healthcare-will-smarter-data-bring-the-a-i-revolution-in-healthcare","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fsynthetic-data-in-healthcare-will-smarter-data-bring-the-a-i-revolution-in-healthcare",{"rendered":17},"What Does Synthetic Data Mean In Healthcare’s Artificial Intelligence Revolution?",{"rendered":19,"protected":20},"\n\u003Ch4 class=\"wp-block-heading\">Data is the foundation of artificial intelligence. As the importance of A.I. grows in modern medicine, there’s a huge need for data (\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdata-annotation\u002F\">as well as data annotation\u003C\u002Fa>) – the latter being one of the most important aspects of the work in building an algorithm. In healthcare, collecting data means utilising existing databases and using images, radiology results, samples, CT or MR scans, patient records and more. The more data you feed the system, the better the results can become. \u003C\u002Fh4>\n\n\n\n\u003Chr class=\"wp-block-separator\"\u002F>\n\n\n\n\u003Cp>Artificial intelligence has earned its place \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F7-things-you-can-expect-from-a-i-in-healthcare\u002F\">in multiple fields of medicine\u003C\u002Fa>, from recognising patterns, supporting diagnoses and setting up treatment pathways to optimising healthcare logistics. Smart algorithms can sift through large volumes of data no man can, deriving clear-cut trends from such analyses. \u003C\u002Fp>\n\n\n\n\u003Cp>It’s easy to guess that this data includes your own health-related data: EMRs, smartwatches, genetic reports, wearables and so on are all means to feed the A.I. with datasets.\u003Cstrong> But what if we would never be able to obtain enough data to contribute to the progress of A.I. in healthcare?\u003C\u002Fstrong> \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>What if privacy concerns don’t allow hospitals to share medical records with companies?\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>That’s when synthetic data comes in.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cdiv style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\">\u003C\u002Fdiv>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Is synthetic data fake?\u003C\u002Fh3>\n\n\n\n\u003Cp>It is fake but it’s based on real-life data. Moreover, it’s possible to use methods that ensure that synthetic data very much resembles the real one. One of these methods is called generative adversarial network (GAN).\u003C\u002Fp>\n\n\n\n\u003Cp>Let’s imagine there’s a painter who wants to create better and better copies of Picasso’s paintings to sell them as real ones. On the other end, there’s a policeman who wants to catch him by spotting these fake Picasso paintings.\u003C\u002Fp>\n\n\n\n\u003Cp>By painting more and more of the fake ones, the painter is getting gradually better and better at creating fakes. At the same time, while going after him, the detective is also getting better at recognising those works of art that are replicas. They both keep trying to beat each other and, after many iterations, the painter creates images indistinguishable from a real Picasso. This was the goal of the \u003Ca href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FGenerative_adversarial_network\">whole experiment\u003C\u002Fa> with machine learning.\u003C\u002Fp>\n\n\n\n\u003Cp>And this is exactly how A.I. can create synthetic photos of birthmarks (or in fact anything else) to ensure the algorithm’s development – in the case of birthmarks, to be able to better detect melanoma or other skin issues. Based on existing data, the algorithm attempts to generate data that is somewhat different from the original, but not so much as to lead to a false result. So it \u003Cem>IS\u003C\u002Fem> fake – but it isn’t.\u003C\u002Fp>\n\n\n\n\u003Cp>As \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41551-021-00751-8?utm_source=pocket_mylist\">this study clearly states\u003C\u002Fa>, “\u003Cem>synthetic data can be created from perturbations using accurate forward models (that is, models that simulate outcomes given specific inputs), physical simulations or A.I.-driven generative models.\u003C\u002Fem>”\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003-768x432.png\" alt=\"\" class=\"wp-image-25289\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003-512x288.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F11\u002F1018_TMF_AI_kiajanlo_003.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Why is data important in healthcare A.I.?\u003C\u002Fh3>\n\n\n\n\u003Cp>The biggest obstacle to A.I. is the inadequacy of the available data. Without patient data, there is no A.I. in healthcare. On one hand, the amount of data needed for effective algorithms in healthcare is crucial as a huge amount of data is needed to feed the algorithms. On the other hand, data needs to be annotated, drawing lines around tumours, pinpointing cells or designating ECG rhythm strips – that’s why the altruistic role of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdata-annotation\u002F\">data annotators\u003C\u002Fa> is so important.\u003C\u002Fp>\n\n\n\n\u003Cp>Above all that, privacy concerns limit the amount of available data in medicine. Working with sensitive patient data is a tricky issue. It seems we cannot keep our privacy intact AND also benefit from A.I.’s advantages in our care. We saw in many cases how sensitive information can get leaked \u003Ca href=\"https:\u002F\u002Fwww.securitymagazine.com\u002Farticles\u002F96399-over-800-million-medical-records-exposed-in-data-breach\">even unintentionally\u003C\u002Fa> – and we are not even talking about hacking or privacy, just a poorly protected database. New methods like \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffederated-learning-can-protect-patients-data-in-hospitals\">federated learning\u003C\u002Fa> might make it possible to do this without breaching patients’ privacy, but its scope is limited.\u003C\u002Fp>\n\n\n\n\u003Cp>That is where synthetic data could be of help. It can fill in the missing data, making it possible to produce entirely fabricated patient datasets that are just as useful for training A.I. as the real thing, while keeping patient data protected.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Privacy, quality and bias\u003C\u002Fh3>\n\n\n\n\u003Cp>With the use of such trained datasets, even the\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fa-i-bias-in-healthcare\"> existing bias\u003C\u002Fa> could be overruled in A.I. programming. There’s an ongoing issue in A.I.-based programming due to the limited access to data focusing on race, skin colour and other matters. An MIT Media Lab \u003Ca href=\"http:\u002F\u002Fgendershades.org\u002F\">study found\u003C\u002Fa> that facial-recognition systems from companies like IBM and Microsoft were 11-19 percent more accurate on lighter-skinned individuals.\u003C\u002Fp>\n\n\n\n\u003Cp>Synthetic data could help overcome this challenge as the training could focus on such variables, making use of real-world environments. Using the above-mentioned example, how to diagnose melanoma on dark skin toned patients – as often \u003Ca href=\"https:\u002F\u002Fwww.vice.com\u002Fen\u002Farticle\u002Fm7evmy\u002Fgoogles-new-dermatology-app-wasnt-designed-for-people-with-darker-skin\">previous algorithms have failed to be able to do so\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"240\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F10-21-2018-Digitalist_Q1_AI-Bias_F-768x240.jpg\" alt=\"A.I. Bias\" class=\"wp-image-24879\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F10-21-2018-Digitalist_Q1_AI-Bias_F-768x240.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F10-21-2018-Digitalist_Q1_AI-Bias_F-1536x480.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F10-21-2018-Digitalist_Q1_AI-Bias_F-512x160.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F10-21-2018-Digitalist_Q1_AI-Bias_F.jpg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption>Source: www.geneticliteracyproject.org\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Hands-on use\u003C\u002Fh3>\n\n\n\n\u003Cp>Synthetic data already has a number of practical use cases. A group of researchers in Michigan have developed a computer vision model to help improve pathologist decision support to more accurately diagnose brain tumours. Their challenge was that if they wanted to use brain scans from other institutions, the algorithm’s efficiency dropped as it could not compare the different types of scans. \u003C\u002Fp>\n\n\n\n\u003Cp>By using synthetic data trained on much larger datasets, their algorithm was “\u003Cem>better able to learn what to look for in our pathology images\u003C\u002Fem>” – Dr. Todd Hollon, neurosurgeon and principal investigator of the machine learning in neurosurgery laboratory at Michigan Medicine \u003Ca href=\"https:\u002F\u002Fwww.healthcareitnews.com\u002Fnews\u002Fsynthetic-data-boosts-accuracy-and-speed-brain-tumor-surgery-cds\">explained\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Chr class=\"wp-block-separator\"\u002F>\n\n\n\n\u003Ch4 class=\"wp-block-heading\">\u003Cstrong>Synthetic data might not be the holy grail for solving all the issues healthcare A.I. programming poses. (\u003C\u002Fstrong>\u003Ca href=\"https:\u002F\u002Ftechmonitor.ai\u002Ftechnology\u002Fai-and-automation\u002Fsynthetic-data-may-not-be-ais-privacy-silver-bullet\">\u003Cstrong>Some even claim\u003C\u002Fstrong>\u003C\u002Fa>\u003Cstrong> it can not effectively add to the privacy issues raised). However, it can provide a wider scope for research and, in principle, add to the protection of privacy in medical data. \u003C\u002Fstrong>\u003C\u002Fh4>\n\n\n\n\u003Cdiv style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\">\u003C\u002Fdiv>\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>Data is the foundation of artificial intelligence. As the importance of A.I. grows in modern medicine, there’s a huge need for data (as well as […]\u003C\u002Fp>\n",6,30807,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32,33],504,499,799,[35,36,37,38,39,40,41],687,7477,821,7479,144,1433,1474,[43,44,45,46,47],947,950,951,952,953,[],[50,51,52,53,54,55,56,57,58,59,60,61,62],1661,3633,1683,6097,1715,1723,1803,1807,1831,1845,1883,2689,2739,[64,14,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84],"post-37443","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-healthcare-design","category-security-privacy","tag-data-privacy","tag-synthetic-data","tag-a-i","tag-gan","tag-artificial-intelligence","tag-privacy","tag-bias","project_category-company","project_category-medical-professionals","project_category-patients","project_category-policy-makers","project_category-researchers",{"id":24,"alt_text":86,"caption":27,"description":27,"media_type":87,"media_details":88,"post":116,"source_url":117},"algorithm, deep learning, tmf","image",{"width":89,"height":90,"file":91,"sizes":92,"image_meta":114},1920,1080,"2020\u002F10\u002F214_tmf-01-1.png",{"medium":93,"large":99,"thumbnail":104,"medium_large":108,"1536x1536":109},{"file":94,"width":95,"height":96,"mime-type":97,"source_url":98},"214_tmf-01-1-370x208.png","370","208","image\u002Fpng","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-370x208.png",{"file":100,"width":101,"height":102,"mime-type":97,"source_url":103},"214_tmf-01-1-768x432.png","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-768x432.png",{"file":105,"width":106,"height":106,"mime-type":97,"source_url":107},"214_tmf-01-1-150x150.png","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-150x150.png",{"file":100,"width":101,"height":102,"mime-type":97,"source_url":103},{"file":110,"width":111,"height":112,"mime-type":97,"source_url":113},"214_tmf-01-1-1536x864.png","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1-1536x864.png",{"aperture":115,"credit":27,"camera":27,"caption":27,"created_timestamp":115,"copyright":27,"focal_length":115,"iso":115,"shutter_speed":115,"title":27,"orientation":115},"0",14484,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1.png",{"subtitle":27,"cta_type":119,"cta_color":27,"related_books":120,"related_posts_footer":123,"related_posts":20},"subscribe",[121,122],24762,30419,[124,125,126],24878,10983,30701,{"yoast_wpseo_title":128,"yoast_wpseo_metadesc":129,"yoast_wpseo_canonical":15},"What Does Synthetic Data Mean In Healthcare’s Artificial Intelligence Revolution? - The Medical Futurist","What if privacy concerns don’t allow hospitals to share medical records with companies? Synthetic data might be the answer.",{"self":131,"collection":137,"about":140,"author":143,"replies":146,"version-history":149,"predecessor-version":153,"wp:featuredmedia":157,"wp:attachment":160,"wp:term":163,"curies":179},[132],{"href":133,"targetHints":134},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F37443",{"allow":135},[136],"GET",[138],{"href":139},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[141],{"href":142},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[144],{"embeddable":26,"href":145},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[147],{"embeddable":26,"href":148},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=37443",[150],{"count":151,"href":152},7,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F37443\u002Frevisions",[154],{"id":155,"href":156},37467,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F37443\u002Frevisions\u002F37467",[158],{"embeddable":26,"href":159},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F30807",[161],{"href":162},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=37443",[164,167,170,173,176],{"taxonomy":165,"embeddable":26,"href":166},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=37443",{"taxonomy":168,"embeddable":26,"href":169},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=37443",{"taxonomy":171,"embeddable":26,"href":172},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=37443",{"taxonomy":174,"embeddable":26,"href":175},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=37443",{"taxonomy":177,"embeddable":26,"href":178},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=37443",[180],{"name":181,"href":182,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[184],{"id":126,"date":185,"date_gmt":186,"guid":187,"modified":189,"modified_gmt":190,"slug":191,"status":13,"type":14,"link":192,"title":193,"content":195,"excerpt":197,"author":199,"featured_media":200,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":201,"categories":202,"tags":213,"project_category":235,"contact_email_category":238,"yst_prominent_words":239,"class_list":245,"better_featured_image":280,"acf":301,"yoast_meta":308,"_links":311},"2020-10-21T10:00:00","2020-10-21T08:00:00",{"rendered":188},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=30701&_wpnonce=de965400f8&status=auto-draft&type=post","2020-10-27T12:20:04","2020-10-27T11:20:04","7-things-you-can-expect-from-a-i-in-healthcare","https:\u002F\u002Fmedicalfuturist.com\u002F7-things-you-can-expect-from-a-i-in-healthcare",{"rendered":194},"7 Things You Can Expect From A.I. In Healthcare",{"rendered":196,"protected":20},"\n\u003Cp>\u003Cem>Note: This is the first part of our series on what A.I. can and can’t do. Check our the \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F7-things-you-cant-expect-from-a-i-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">second part here\u003C\u002Fa>!\u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cp>Artificial Intelligence (A.I.) has for long been the subject of the fertile minds of science-fiction writers and movie directors. HAL 9000, Skynet and JARVIS are some of the many A.I. names sci-fi enthusiasts are familiar with. They streamline administrative tasks, entertain humans and, of course, become overlords threatening human existence. \u003C\u002Fp>\n\n\n\n\u003Cp>Now, thanks to technological progress, such A.I. are breaking out of the confines of movies and books and into healthcare. While they aren’t threatening our existence, they are helping in improving the medical field. From forecasting disease outbreaks to helping in new drug discovery, the potential of A.I. in healthcare is attracting \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.statista.com\u002Fstatistics\u002F826993\u002Fhealth-ai-market-value-worldwide\u002F\" target=\"_blank\">massive investments\u003C\u002Fa> and increasing \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fnew-study-the-state-of-artificial-intelligence-based-fda-approved-medical-devices-and-algorithms-an-online-database\" target=\"_blank\">life science research\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002FAI-and-COVID-small-768x432.png\" alt=\"artificial intelligence and COVID\" class=\"wp-image-27609\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002FAI-and-COVID-small-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002FAI-and-COVID-small-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002FAI-and-COVID-small-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002FAI-and-COVID-small.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>However, healthcare A.I. is a relatively juvenile field and the technology’s potentials might not be so clear-cut. This is largely influenced by A.I.’s exaggerated depiction and hype in popular media or simply due to poor understanding of the technology. As such, a clear picture of where we are heading with A. I. in healthcare can prove to be practical for medical professionals and patients alike. \u003C\u002Fp>\n\n\n\n\u003Cp>That’s the aim of this series of articles about the potential of A.I. in healthcare in the next decade or so. In this first article, we summarise 7 things this technology can bring to the field. And we discuss 7 things you can’t expect in the next piece, along with recommendations to prepare for the age of A.I.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The 7 things you can definitely expect\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Smart algorithms can sift through large volumes of data more quickly than humans ever can and derive trends from these analyses. Many of the possibilities listed below are still experimental or implemented on a small scale. But it’s only a matter of time before they are refined and deployed for wider adoption.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>1. Better organised healthcare logistics\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Annually, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.wsj.com\u002Farticles\u002Fdoctor-visits-could-provide-relief-to-uber-and-lyft-11562756401\" target=\"_blank\">some 3.6 million U.S. patients\u003C\u002Fa> miss their doctor’s appointment as a result of poor transportation services. However, even those who make it to those appointments are met with the inevitable waiting times. 97% of the 5000+ patients involved in \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.softwareadvice.com\u002Fresources\u002Fhow-to-treat-patient-wait-time-woes\u002F\" target=\"_blank\">a Software Advice survey\u003C\u002Fa> reported feeling frustrated by wait times at the doctor’s office. It’s not hard to relate. But when it comes down to it, those are logistics issues that can be enhanced with better organisation.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber-768x432.jpg\" alt=\"\" class=\"wp-image-17697\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber-512x288.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber-444x250.jpg 444w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2018\u002F04\u002Ffuture-of-ambulance-and-uber.jpg 870w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>By integrating an A.I. assistant into the healthcare system, it could guide patients and optimise the time spent during their medical journey with \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fcan-we-eliminate-waiting-times-from-healthcare-forever\u002F\" target=\"_blank\">a Waze-like approach\u003C\u002Fa>. It can determine where the queue is shorter and which test will take less time to perform for each patient. By connecting with \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fride-hailing-platforms-solve-problems-transportation-healthcare\u002F\" target=\"_blank\">non-emergency medical transportation (NEMT) rides\u003C\u002Fa> offered by ride-hailing platforms like Uber and Lyft, the algorithm can suggest which healthcare facility will be more time-efficient to visit and direct patients there. In this way, the time spent by each patient is optimised while they have a better healthcare experience.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>2. Boosting drug design to a new level\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Estimates put the numbers at \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2452302X1600036X#:~:text=Although%20the%20drug%20development%20takes,daunting%20and%20difficult%20to%20navigate.\" target=\"_blank\">about 12 years\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.fiercebiotech.com\u002Fr-d\u002Faverage-cost-of-drug-r-d-try-2-9b-on-for-size\" target=\"_blank\">$2.9 billion\u003C\u002Fa> for an experimental drug to advance from concept to market. This takes into account the time and resources invested in finding suitable candidates, addressing unexpected side effects in clinical trials and the multiple trial-and-error sequences. But with A.I., these numbers can be significantly slashed.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004-768x432.png\" alt=\"\" class=\"wp-image-28737\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F06\u002Fpicture_004.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>As a proof-of-concept, the A.I. pharma startup Insilico Medicine identified a potential new drug \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.technologyreview.com\u002F2019\u002F09\u002F03\u002F133175\u002Fan-ai-system-identified-a-potential-new-drug-in-just-46-days\u002F\" target=\"_blank\">in only 46 days\u003C\u002Fa>. Its software achieved this by analysing hordes of data which would take humans years to go through. During the Ebola epidemic in 2015, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.atomwise.com\u002F2015\u002F03\u002F24\u002Fnew-ebola-treatment-using-artificial-intelligence\u002F\" target=\"_blank\">Atomwise used its A.I. algorithm\u003C\u002Fa> to identify two drugs with significant potential to reduce Ebola infectivity. It accomplished this effort in less than a day. With the potential that A.I. holds in drug discovery, it’s no mere coincidence that \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fblog.benchsci.com\u002Fstartups-using-artificial-intelligence-in-drug-discovery\" target=\"_blank\">over 230 startups\u003C\u002Fa> are using the technology for this purpose.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>3. Improve working conditions for medical professionals while saving lives\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fartificial-intelligence-could-solve-alarm-fatigue-in-hospitals\u002F\" target=\"_blank\">Alarm fatigue\u003C\u002Fa> is an endemic problem among healthcare workers. It refers to the point where they become desensitised to alarm signs due to being exposed to incessant beeping alerts throughout the day. Some experience up to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC4206416\u002F\" target=\"_blank\">187 alarms per bed per day\u003C\u002Fa>; of which \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnurse.org\u002Farticles\u002Falarm-fatigue-statistics-patient-safety\u002F\" target=\"_blank\">72% to 99%\u003C\u002Fa> are false alarms. With the medical staff overburdened as they are, alarm fatigue predisposes them to miss that small fraction of alerts that do require medical attention. A study put those so-called “alarm-related deaths” to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fasa.scitation.org\u002Fdoi\u002Fabs\u002F10.1121\u002F1.4950561\" target=\"_blank\">about 200 per year\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small-768x432.png\" alt=\"alarm fatigue\" class=\"wp-image-26271\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small-512x288.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F02\u002Falarm-fatigue-small.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>How about hearing 99% fewer alarms but only hearing that 1% that are clinically actionable? Researchers developed an A.I. that does just that and published their findings \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.jmir.org\u002F2019\u002F11\u002Fe15406\" target=\"_blank\">in a paper\u003C\u002Fa>. Their automatic reasoning mechanism helped reduce notifications received by caregivers by up to 99.3%. Such a feature will greatly improve working conditions in hospitals so that the staff can focus on those cases that require attention. Given those advantages, it’s easy to see this feature getting implemented.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>4. Finding new associations between risks and diseases\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>With their ability to analyse information, recognise patterns and derive trends in ways that humans can’t, A. I.-based algorithms can surprise us with new associations in medicine. For example, Google researchers \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-curious-case-of-a-i-discovering-unusual-associations-in-medicine\u002F\" target=\"_blank\">fed retinal images to an A.I.\u003C\u002Fa> to identify long-term health dangers. After going through enough data, the algorithm taught itself what to look for in retinal images to detect those with signs of cardiovascular risks.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-768x432.jpg\" alt=\"AI association\" class=\"wp-image-27237\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small-1536x864.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002FAI-association-small.jpg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>In another case, researchers at the University of California in San Francisco \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalxpress.com\u002Fnews\u002F2018-11-artificial-intelligence-alzheimer-years-diagnosis.html\" target=\"_blank\">trained an algorithm\u003C\u002Fa> to recognise metabolic patterns associated with Alzheimer’s disease from brain scans. In later tests, the A.I. detected the condition about six years before the final diagnosis, with 100% sensitivity.\u003C\u002Fp>\n\n\n\n\u003Cp>There have been several such instances of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-curious-case-of-a-i-discovering-unusual-associations-in-medicine\u002F\" target=\"_blank\">A.I. discovering unusual associations in medicine\u003C\u002Fa>; and we will likely come across more as the technology gets more widely adopted.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>5. Ushering the new era of the art of medicine\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Many might think that A.I. will strip the art of medicine from healthcare practice by taking over the tasks that medical professionals have been traditionally handling. On the contrary, it will facilitate \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fartificial-intelligence-and-the-art-of-medicine\u002F\" target=\"_blank\">the real era of the art of medicine\u003C\u002Fa>. Bureaucratic tasks and managing health IT and EHR systems are among the major reported causes of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fphysician-burnout\u002F\" target=\"_blank\">physician burnout\u003C\u002Fa>. But these aren’t related to the practice of medicine. Such mundane administrative tasks can be automated with algorithms, which will free up valuable time; time that physicians can subsequently dedicate to their patients and elucidating medical conditions.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine-768x432.png\" alt=\"art of medicine\" class=\"wp-image-23755\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F04\u002F083_the_art_of_medicine.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>A.I. algorithms can further assist in decision-making to improve the accuracy of diagnoses. For instance, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.futurity.org\u002Fartificial-intelligence-breast-cancer-detection-2261322\u002F#:~:text=boosts%20breast%20cancer%20detection%20accuracy,-January%2022nd%2C%202020&text=An%20artificial%20intelligence%20tool%E2%80%94trained,analysis%2C%20a%20new%20study%20finds.\" target=\"_blank\">several\u003C\u002Fa> \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.healthcareitnews.com\u002Fnews\u002Fasia-pacific\u002Fai-helps-radiologists-improve-accuracy-breast-cancer-detection-lesser-recalls\" target=\"_blank\">studies\u003C\u002Fa> show that with the help of A.I., radiologists improve the accuracy of cancer detection from radiological scans. In future scenarios, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fartificial-intelligence-and-the-art-of-medicine\u002F\" target=\"_blank\">medical A.I. trained via reinforcement learning\u003C\u002Fa> could discover treatments and cures for conditions when human medical professionals could not. Cracking the reasoning behind such unconventional and novel approaches will herald the true era of art in medicine.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>6. Help forecast future outbreaks and pandemics\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>You might be familiar with this story by now; before either the WHO or the CDC issued warnings about COVID-19’s spread, it was Bluedot, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-digital-health-technology-can-help-manage-the-coronavirus-outbreak\" target=\"_blank\">an A.I. company that did so\u003C\u002Fa>. Their algorithm went through news reports, airline data, and reports of animal disease outbreaks to detect trends. These were then analysed by epidemiologists who then alerted the company’s clients.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"254\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002Fcovid-19-ai-768x254.jpg\" alt=\"\" class=\"wp-image-27593\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002Fcovid-19-ai-768x254.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F04\u002Fcovid-19-ai.jpg 870w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption>Source: https:\u002F\u002Fwww.coe.int\u002F\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>As the virus spread, other organisations employed similar solutions. Soon after it appeared, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.worldpop.org\u002Fevents\u002Fchina\" target=\"_blank\">researchers fed an algorithm\u003C\u002Fa> with anonymised air travel and smartphone movement data to explore how the disease could spread from Wuhan to other cities. Another team \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.medrxiv.org\u002Fcontent\u002F10.1101\u002F2020.01.30.20019844v4\" target=\"_blank\">used an A.I. to model COVID-19’s spread\u003C\u002Fa> from case reports, human movement and public health interventions. This helped show how travel restrictions limited the contagion’s spread.\u003C\u002Fp>\n\n\n\n\u003Cp>Given that \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-sober-state-of-artificial-intelligence-in-the-fight-against-covid-19\u002F\" target=\"_blank\">A.I.’s contribution\u003C\u002Fa> became evident during the current pandemic, authorities will likely invest more in such forecasting methods. This will give them better insight into forthcoming disease outbreaks and better prepare for any eventuality.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>7. To get unbeatable at specific, data-oriented tasks\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>When softwares like IBM’s DeepBlue or Google’s AlphaGo \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Falphago-artificial-intelligence-in-healthcare\u002F\" target=\"_blank\">beat world champions at games\u003C\u002Fa> such as chess or Go, it sends a strong message that algorithms will become unbeatable in specific, data-oriented tasks. This is what software described as \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fa-physicians-visual-guide-to-artificial-intelligence\" target=\"_blank\">Artificial Narrow Intelligence\u003C\u002Fa> (ANI) excel at.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F05\u002FAI-doctor-image-768x432.jpg\" alt=\"\" class=\"wp-image-28295\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F05\u002FAI-doctor-image-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F05\u002FAI-doctor-image-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F05\u002FAI-doctor-image-1536x864.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F05\u002FAI-doctor-image.jpg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>Such algorithms can analyse the ever-increasing volume of medical information and research data, which is humanly impossible to do. From the insights gained, we can better understand complex conditions like cancer, which researchers are constantly making new discoveries about.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>To be continued…\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>That’s a wrap for the first article in this series. We got acquainted with the possibilities healthcare A.I. holds. Despite these being manifold, there are also limitations to what A.I. can achieve in healthcare. That’s the subject of the second entry to this series. \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F7-things-you-cant-expect-from-a-i-in-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">Be sure to check it out\u003C\u002Fa>!\u003C\u002Fp>\n",{"rendered":198,"protected":20},"\u003Cp>Note: This is the first part of our series on what A.I. can and can’t do. Check our the second part here! Artificial Intelligence (A.I.) […]\u003C\u002Fp>\n",16,30779,{"_acf_changed":20,"footnotes":27},[31,203,204,205,32,206,207,208,209,210,211,33,212],798,491,521,800,516,489,497,512,515,494,[214,215,216,217,218,219,220,221,222,223,224,225,226,227,37,228,229,230,231,232,233,234],6287,222,6289,281,3085,771,6291,6293,1142,6295,1168,6297,1224,4247,6299,1438,1530,6091,6281,6285,134,[43,236,237,44,45,46,47],948,949,[],[240,241,242,243,244,50,52,55],1739,3193,3195,3555,5489,[246,14,65,66,67,68,69,70,247,248,249,71,250,251,252,253,254,255,72,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,75,271,272,273,274,275,276,277,80,278,279,81,82,83,84],"post-30701","category-digital-health-research","category-empowered-patients","category-future-medicine","category-healthcare-policy","category-medical-education","category-personalized-medicine","category-portable-diagnostics","category-robotics","category-science-fiction","category-telemedicine","tag-skynet","tag-ebola","tag-nemt","tag-ibm","tag-covid19","tag-ani","tag-insilico-medicine","tag-atomwise","tag-life-sciences","tag-alarm-fatigue","tag-smart-algorithm","tag-ibm-deepblue","tag-physician-burnout","tag-pandemic","tag-alphago","tag-outbreak","tag-drug-design","tag-google-a-i","tag-jarvis","tag-hal-9000","tag-ai","project_category-developers","project_category-educators",{"id":200,"alt_text":281,"caption":27,"description":282,"media_type":87,"media_details":283,"post":126,"source_url":300},"things you can and can't expect from A.I.","Offering a clear picture of where we are heading with A. I. in healthcare, part two: 7 things you can not expect from artificial intelligence in healthcare.",{"width":89,"height":90,"file":284,"sizes":285,"image_meta":299},"2020\u002F10\u002F214_tmf-01.png",{"medium":286,"large":289,"thumbnail":292,"medium_large":295,"1536x1536":296},{"file":287,"width":95,"height":96,"mime-type":97,"source_url":288},"214_tmf-01-370x208.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-370x208.png",{"file":290,"width":101,"height":102,"mime-type":97,"source_url":291},"214_tmf-01-768x432.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-768x432.png",{"file":293,"width":106,"height":106,"mime-type":97,"source_url":294},"214_tmf-01-150x150.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-150x150.png",{"file":290,"width":101,"height":102,"mime-type":97,"source_url":291},{"file":297,"width":111,"height":112,"mime-type":97,"source_url":298},"214_tmf-01-1536x864.png","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01-1536x864.png",{"aperture":115,"credit":27,"camera":27,"caption":27,"created_timestamp":115,"copyright":27,"focal_length":115,"iso":115,"shutter_speed":115,"title":27,"orientation":115},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F214_tmf-01.png",{"cta_type":119,"cta_color":27,"subtitle":27,"related_books":302,"related_posts_footer":304,"related_posts":20},[121,303],24763,[305,306,307],13650,10785,30149,{"yoast_wpseo_title":309,"yoast_wpseo_metadesc":310,"yoast_wpseo_canonical":192},"7 Things You Can Expect From A.I. In Healthcare - The Medical Futurist","Offering a clear picture on where we are heading with A. I. in healthcare, part one: 7 things you can expect from artificial intelligence in healthcare.",{"self":312,"collection":317,"about":319,"author":321,"replies":324,"version-history":327,"predecessor-version":331,"wp:featuredmedia":335,"wp:attachment":338,"wp:term":341,"curies":352},[313],{"href":314,"targetHints":315},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F30701",{"allow":316},[136],[318],{"href":139},[320],{"href":142},[322],{"embeddable":26,"href":323},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[325],{"embeddable":26,"href":326},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=30701",[328],{"count":329,"href":330},10,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F30701\u002Frevisions",[332],{"id":333,"href":334},30887,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F30701\u002Frevisions\u002F30887",[336],{"embeddable":26,"href":337},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F30779",[339],{"href":340},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=30701",[342,344,346,348,350],{"taxonomy":165,"embeddable":26,"href":343},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=30701",{"taxonomy":168,"embeddable":26,"href":345},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=30701",{"taxonomy":171,"embeddable":26,"href":347},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=30701",{"taxonomy":174,"embeddable":26,"href":349},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=30701",{"taxonomy":177,"embeddable":26,"href":351},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=30701",[353],{"name":181,"href":182,"templated":26},[355],{"id":122,"date":356,"date_gmt":357,"guid":358,"modified":360,"modified_gmt":361,"slug":362,"status":13,"type":363,"link":364,"title":365,"content":367,"excerpt":369,"author":23,"featured_media":371,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":372,"class_list":375,"better_featured_image":378,"acf":398,"yoast_meta":420,"_links":423},"2020-10-01T10:54:54","2020-10-01T08:54:54",{"rendered":359},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=30419","2023-03-12T18:16:29","2023-03-12T17:16:29","privacy-in-digital-health","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fprivacy-in-digital-health\u002F",{"rendered":366},"Hackers, Breaches and the Value of Health Data",{"rendered":368,"protected":20},"\n\u003Cp>Today, everyone needs to understand that there is no digital health without sacrificing a part of our privacy. The advanced technologies fueling the transformation cannot improve without our data; and without it, they can’t be implemented as part of regular medical care. And COVID-19 has only made things worse.\u003C\u002Fp>\n\n\n\n\u003Cp>In this e-Book, we defined the three cornerstones of privacy of every privacy discussion going forward: the traditional, the new and the future spheres that deal with your health data, and put forward recommendations on how you can start protecting yourself.\u003C\u002Fp>\n",{"rendered":370,"protected":20},"\u003Cp>Today, everyone needs to understand that there is no digital health without sacrificing a part of our privacy. The advanced technologies fueling the transformation cannot […]\u003C\u002Fp>\n",49967,[373,374,51],1693,1571,[376,363,377,66,68,69],"post-30419","type-book",{"id":371,"alt_text":27,"caption":27,"description":27,"media_type":87,"media_details":379,"post":122,"source_url":397},{"width":380,"height":381,"file":382,"filesize":383,"sizes":384,"image_meta":395},320,414,"2020\u002F10\u002Fhack-breaches-health-data.png",89249,{"medium":385,"thumbnail":390},{"file":386,"width":380,"height":387,"mime-type":97,"filesize":388,"source_url":389},"hack-breaches-health-data-320x208.png",208,53801,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data-320x208.png",{"file":391,"width":392,"height":392,"mime-type":97,"filesize":393,"source_url":394},"hack-breaches-health-data-150x150.png",150,20987,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data-150x150.png",{"aperture":115,"credit":27,"camera":27,"caption":27,"created_timestamp":115,"copyright":27,"focal_length":115,"iso":115,"shutter_speed":115,"title":27,"orientation":115,"keywords":396},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002Fhack-breaches-health-data.png",{"buy_button_text":399,"leanpub_url":400,"preview":401},"Get it on Leanpub","https:\u002F\u002Fleanpub.com\u002Fprivacy-in-digital-health\u002F",[402,404,406,408,410,412,414,416,418],{"image":403},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-01.png",{"image":405},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-03.png",{"image":407},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-04.png",{"image":409},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-05.png",{"image":411},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-06.png",{"image":413},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-07.png",{"image":415},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-08.png",{"image":417},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-09.png",{"image":419},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F0930_PRIVACY_TMF_EBOOK-10.png",{"yoast_wpseo_title":421,"yoast_wpseo_metadesc":422,"yoast_wpseo_canonical":364},"Hackers, Breaches and the Value of Health Data: What You Need To Know - The Medical Futurist","Privacy in Digital Health: Privacy and security issues pertaining to the digital health era are complex and multifactorial. Learn more from our book",{"self":424,"collection":429,"about":432,"author":435,"replies":437,"wp:featuredmedia":440,"wp:attachment":443,"wp:term":446,"curies":449},[425],{"href":426,"targetHints":427},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F30419",{"allow":428},[136],[430],{"href":431},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[433],{"href":434},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[436],{"embeddable":26,"href":145},[438],{"embeddable":26,"href":439},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=30419",[441],{"embeddable":26,"href":442},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49967",[444],{"href":445},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=30419",[447],{"taxonomy":177,"embeddable":26,"href":448},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=30419",[450],{"name":181,"href":182,"templated":26},1790254545386]