[{"data":1,"prerenderedAt":395},["ShallowReactive",2],{"slug-danger-alert-ai-is-writing-content-but-its-lying-let-us-show-you-how":3},{"post":4,"relatedPosts":165,"relatedBooks":312},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":33,"project_category":39,"contact_email_category":42,"yst_prominent_words":43,"class_list":50,"better_featured_image":66,"acf":99,"yoast_meta":109,"_links":112},47975,"2022-11-15T10:00:00","2022-11-15T09:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=47975&_wpnonce=9edddd52c8&status=auto-draft&type=post","2022-11-15T11:32:53","2022-11-15T10:32:53","danger-alert-ai-is-writing-content-but-its-lying-let-us-show-you-how","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fdanger-alert-ai-is-writing-content-but-its-lying-let-us-show-you-how",{"rendered":17},"Danger Alert: AI Is Writing Content, But It’s Lying – Let Us Show You How",{"rendered":19,"protected":20},"\n\u003Cp>There is a growing number of AI text generators around the web, offering more or less the same. \u003C\u002Fp>\n\n\n\n\u003Col class=\"wp-block-list\">\u003Cli>You give a brief of your planned content and maybe some keywords\u003C\u002Fli>\u003Cli>Set the parameters, like the language, the tone of the text and the creativity level\u003C\u002Fli>\u003Cli>Hit enter\u003C\u002Fli>\u003Cli>Voila, you get your blog post\u002Farticle\u002Fmarketing copy\u002Fwhatever\u003C\u002Fli>\u003C\u002Fol>\n\n\n\n\u003Cp>Isn’t it amazing? Writing a good text takes effort, so outsourcing it to AI could save us a ton of time in researching and crafting content. \u003C\u002Fp>\n\n\n\n\u003Cp>Before you quickly lay off all your writers, let me show through a few examples of why trusting A.I. with content is dangerous as of now. TLDR spoiler: it is lying. All right, confabulating. Using alternative facts. \u003C\u002Fp>\n\n\n\n\u003Cp>We tested the most popular AI text generator tools, choosing a medical topic, where it is clear how these fabricated “facts” can be extremely dangerous. The topic pick was a recent breakthrough, where the number of publications is yet limited, so it is relatively easy to fact-check the AI-generated outputs. \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\u002F2020\u002F10\u002F216_tmf-01-768x432.png\" alt=\"AI text generators might end up in healthcare\" class=\"wp-image-30867\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F216_tmf-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F216_tmf-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F216_tmf-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F10\u002F216_tmf-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption>Is this a real doctor or an algorithm?  \u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>We tried the five AI text generators that were most often recommended on professional-looking sites. Where there was an option, we both tested the “factual’ and the “optimal” creativity setting. The results haven’t really differed. \u003C\u002Fp>\n\n\n\n\u003Cp>We tested: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>Simplified\u003C\u002Fli>\u003Cli>Rytr\u003C\u002Fli>\u003Cli>Smart Copy\u003C\u002Fli>\u003Cli>Copy.ai\u003C\u002Fli>\u003Cli>Contentbot.ai\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cp>As the outputs of the five solutions highlighted very similar flaws (and dangers), let’s stick with three examples, for the sake of keeping the article within a reasonable length. Trust me, the rest didn’t do any better.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">The topic: \u003C\u002Fh3>\n\n\n\n\u003Cp>We went with this \u003Ca href=\"https:\u002F\u002Fwww.bbc.com\u002Fnews\u002Fhealth-63513330\" target=\"_blank\" rel=\"noreferrer noopener\">relatively recent announcement\u003C\u002Fa>: a few days ago UK researchers transplanted lab-grown blood into human patients in a world-first trial. So the brief was this: “Lab-grown blood transplanted into humans”.\u003C\u002Fp>\n\n\n\n\u003Cp>The main facts of the original article (and the breakthrough) are this:\u003C\u002Fp>\n\n\n\n\u003Col class=\"wp-block-list\">\u003Cli>A UK research team transplanted lab-grown blood in very small amounts (5-10ml) into two healthy patients\u003C\u002Fli>\u003Cli>The trial seems to have gone well\u003C\u002Fli>\u003Cli>The team used stem cells to grow them into red blood cells\u003C\u002Fli>\u003C\u002Fol>\n\n\n\n\u003Cp>And let’s see what the content generator algorithms came up with. In all the generated texts we will \u003Cstrong>bold the sections \u003C\u002Fstrong>that have nothing to do with the actual facts. These are things AI just produced. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Simplified – AI text generator:\u003C\u002Fh3>\n\n\n\n\u003Cp>“In a world first, laboratory-grown blood cells have been transplanted into a human patient. The groundbreaking procedure, which was conducted at Addenbrooke’s Hospital in Cambridge, could help to pave the way for new treatments for blood disorders.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>The patient, who\u003C\u002Fstrong> has not been named, \u003Cstrong>suffered from beta thalassemia\u003C\u002Fstrong>, a condition that results in the production of abnormal red blood cells. \u003Cstrong>In order to treat the condition, the patient underwent a procedure in which laboratory-grown blood cells were injected into their bloodstream.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>This is the first time that lab-grown blood cells have been used to treat a human patient, and it represents a significant milestone in the field of regenerative medicine. With further research and development, it is hoped that this technique could be used to treat a range of other blood disorders.\u003C\u002Fp>\n\n\n\n\u003Cp>The \u003Cstrong>Australian team is now working on expanding the clinical trials to include more patients. \u003C\u002Fstrong>If all goes well, we may see lab-grown blood become a regular treatment for blood disorders in the not-too-distant future.”\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">What is wrong with it?\u003C\u002Fh3>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>According to the original article, researchers transplanted the blood into two healthy individuals\u003C\u002Fli>\u003Cli>Although beta thalassemia is indeed a serious disorder and is connected to blood cells, it has nothing to do with the lab-grown blood transplantation\u003C\u002Fli>\u003Cli>Not to mention how Australia ended up in the text, as the trial took place in the UK\u003C\u002Fli>\u003C\u002Ful>\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\u002F2021\u002F02\u002Ftmf_article_246-01-768x432.png\" alt=\"\" class=\"wp-image-32755\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_246-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_246-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_246-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_246-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Rytr – AI text generator:\u003C\u002Fh3>\n\n\n\n\u003Cp>“Blood transfusions are not a new invention. In fact, the first successful blood transfusion was done in 1667 by Jean-Baptiste Denis. However, we now have a new type of blood transfusion that is being tested on humans: lab-grown blood.\u003C\u002Fp>\n\n\n\n\u003Cp>Lab-grown blood is created using stem cells and it is possible to produce large quantities of this type of blood without any risk to the donor. The research on this topic has been going on for a while and there are many trials being run.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>In 2016, the first human trial was successfully completed by the Japanese company Kaneka Corporation with Dr. Takanori Takebe as their lead researcher. They used lab-grown erythrocytes in patients with thalassemia major and it proved successful in reducing their need for regular transfusions from one per week to one per three months or even less often than that!”\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">What is wrong with it?\u003C\u002Fh3>\n\n\n\n\u003Cp>Well, mostly everything. \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>Although there is a Japanese company called Kaneka, it doesn’t have much to do with healthcare and nothing with dr. Takanori Takebe (as long as Google can be trusted to find a connection between them)\u003C\u002Fli>\u003Cli>There is a Dr Takanori Takebe, but although I researched for a while, he never seems to have published anything related to erythrocytes\u003C\u002Fli>\u003Cli>Then again, we have thalassemia major\u003C\u002Fli>\u003Cli>And the completely fake claim that there was a procedure that successfully reduced thalassemia patients’ need for regular transfusions from one per week to one every 3 months\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Copy.ai – AI text generator:\u003C\u002Fh3>\n\n\n\n\u003Cp>“Scientists are trying to figure out how to make more blood, and they think they might have found a solution. In a recent trial, researchers gave lab-grown blood cells \u003Cstrong>to people who had lost too much of their own blood. The results were mixed: some patients did well with the cells, but others died because the transplant didn’t work properly. \u003C\u002Fstrong>This research is still in its early stages, so we don’t know what will happen if it’s tried again with more patients or other kinds of stem cells. Still, it’s exciting because \u003Cstrong>it shows that scientists are making progress towards curing serious diseases like sickle cell anemia \u003C\u002Fstrong>by using stem cells as treatments rather than just research tools!\u003C\u002Fp>\n\n\n\n\u003Cp>[here the text generator added some fascinating and completely unrelated paragraphs I skip for now to get to the point of the “article”]\u003C\u002Fp>\n\n\n\n\u003Cp>The patient received the lab-grown blood transfusion on\u003Cstrong> March 11th at the University of Minnesota Medical Center\u003C\u002Fstrong>. The goal was to see if this approach could be used as a way to safely deliver red blood cells to patients with blood disorders, like sickle cell disease or thalassemia, who need transfusions but for whom donated blood is not an option.\u003C\u002Fp>\n\n\n\n\u003Cp>The trial was successful in that it showed that lab-grown cells can be made into mature red blood cells and then used effectively by patients. But it didn’t go exactly as planned: \u003Cstrong>The patient developed an infection after receiving his transfusion, which is not uncommon for this type of procedure (many other trials have shown similar complications). That infection cleared up with treatment from antibiotics and antiviral drugs. Now he’s doing well and looking forward to going back home from the hospital later this week.”\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">What is wrong with it?\u003C\u002Fh3>\n\n\n\n\u003Cp>That is a long list. \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>There were no trial participants who lost too much blood\u003C\u002Fli>\u003Cli>No one died \u003C\u002Fli>\u003Cli>The research on lab-grown blood is just in too early a phase to conclude they made progress towards curing sickle cell anaemia \u003C\u002Fli>\u003Cli>The date and the location are fabricated \u003C\u002Fli>\u003Cli>Luckily, by the end of the article, the patient recovered from dying but required all kinds of treatments  \u003C\u002Fli>\u003Cli>And of course, as the patient is non-existent, they can hardly have said they are looking forward to going home from the hospital\u003C\u002Fli>\u003C\u002Ful>\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\u002F2021\u002F02\u002Ftmf_article_243-01-768x432.png\" alt=\"\" class=\"wp-image-32629\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Ftmf_article_243-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">What if synthetic healthcare workers will fill the gaps with alternative facts?\u003C\u002Fh3>\n\n\n\n\u003Cp>As synthetic media and AI content generation starts to become a thing, we better learn the limitations of these tools. Although creating beauty listicles with AI to make your job easy is not nice (Top 12 skin care tips for dry skin in the winter – anyone?), it will hopefully not endanger others. Although, I’m not even sure about that.\u003C\u002Fp>\n\n\n\n\u003Cp>But as we have seen, AI- creates trustworthy-looking texts about healthcare topics (and about finances, and so many other things) that are just not factual. \u003C\u002Fp>\n\n\n\n\u003Cp>There is so much talk about how synthetic media will enter healthcare and how algorithms will become our new colleagues. And that is fine if we talk about artificial narrow intelligence – chatbots that are trained to assist users in well-defined topics with a pre-set batch of information. \u003C\u002Fp>\n\n\n\n\u003Cp>But imagine such AI algorithms stepping in and answering people’s questions about the latest treatments. \u003C\u002Fp>\n\n\n\n\u003Cp>It comes up with false claims – how lab-grown blood has cured leukaemia and beta-thalassemia patients, it creates connections between companies and researchers and research topics that were never connected. \u003C\u002Fp>\n\n\n\n\u003Cp>I have no illusions. AI content generation WILL soon become pretty mainstream. We soon will be flooded with even more fake info than ever before. We all need to learn – or reinforce our habits – to check the sources of information. Beware, my friends. AI is here, it is generating content, and it is lying. The more you know about it, the better you will be prepared to not trust everything you read. \u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>Before you quickly lay off all your writers, let me show through a few examples of why trusting AI with content is dangerous as of now. TLDR spoiler: it is lying.  We tested AI text generators with some medical content, and the result is worrysome. \u003C\u002Fp>\n",6,47983,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32],7079,504,[34,35,36,37,38],134,144,7687,7689,7691,[40,41],950,951,[],[44,45,46,47,48,49],1833,2877,2941,2943,2947,2963,[51,14,52,53,54,55,56,57,58,59,60,61,62,63,64,65],"post-47975","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-ai-text-generator","tag-synthetic-media","tag-ai-in-heaalthcare","project_category-medical-professionals","project_category-patients",{"id":24,"alt_text":67,"caption":27,"description":27,"media_type":68,"media_details":69,"post":5,"source_url":98},"robot android artificial intelligence AI algorithm human people man woman","image",{"width":70,"height":71,"file":72,"sizes":73,"image_meta":95},6667,3750,"2022\u002F11\u002Ftmf_article_339-01.png",{"medium":74,"large":80,"thumbnail":85,"medium_large":89,"1536x1536":90},{"file":75,"width":76,"height":77,"mime-type":78,"source_url":79},"tmf_article_339-01-370x208.png",370,208,"image\u002Fpng","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01-370x208.png",{"file":81,"width":82,"height":83,"mime-type":78,"source_url":84},"tmf_article_339-01-768x432.png",768,432,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01-768x432.png",{"file":86,"width":87,"height":87,"mime-type":78,"source_url":88},"tmf_article_339-01-150x150.png",150,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01-150x150.png",{"file":81,"width":82,"height":83,"mime-type":78,"source_url":84},{"file":91,"width":92,"height":93,"mime-type":78,"source_url":94},"tmf_article_339-01-1536x864.png",1536,864,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01-1536x864.png",{"aperture":96,"credit":27,"camera":27,"caption":27,"created_timestamp":96,"copyright":27,"focal_length":96,"iso":96,"shutter_speed":96,"title":27,"orientation":96,"keywords":97},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F11\u002Ftmf_article_339-01.png",{"cta_type":100,"cta_color":27,"related_books":101,"related_posts_footer":105,"related_posts":20,"subtitle":27},"subscribe",[102,103,104],30419,24761,24765,[106,107,108],47785,47495,46538,{"yoast_wpseo_title":110,"yoast_wpseo_metadesc":111,"yoast_wpseo_canonical":15},"Danger Alert: AI Is Writing Content, But It’s Lying - Let Us Show You How","We tested the five most recommended AI text generators with some medical content, and the result is worrysome. TLDR: beware of AI, it's lying!",{"self":113,"collection":119,"about":122,"author":125,"replies":128,"version-history":131,"predecessor-version":135,"wp:featuredmedia":139,"wp:attachment":142,"wp:term":145,"curies":161},[114],{"href":115,"targetHints":116},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47975",{"allow":117},[118],"GET",[120],{"href":121},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[123],{"href":124},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[126],{"embeddable":26,"href":127},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[129],{"embeddable":26,"href":130},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=47975",[132],{"count":133,"href":134},24,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47975\u002Frevisions",[136],{"id":137,"href":138},51675,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47975\u002Frevisions\u002F51675",[140],{"embeddable":26,"href":141},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F47983",[143],{"href":144},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=47975",[146,149,152,155,158],{"taxonomy":147,"embeddable":26,"href":148},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=47975",{"taxonomy":150,"embeddable":26,"href":151},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=47975",{"taxonomy":153,"embeddable":26,"href":154},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=47975",{"taxonomy":156,"embeddable":26,"href":157},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=47975",{"taxonomy":159,"embeddable":26,"href":160},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=47975",[162],{"name":163,"href":164,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[166],{"id":108,"date":167,"date_gmt":168,"guid":169,"modified":171,"modified_gmt":172,"slug":173,"status":13,"type":14,"link":174,"title":175,"content":177,"excerpt":179,"author":23,"featured_media":181,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":182,"categories":183,"tags":188,"project_category":199,"contact_email_category":201,"yst_prominent_words":202,"class_list":209,"better_featured_image":226,"acf":262,"yoast_meta":268,"_links":270},"2022-05-31T10:00:00","2022-05-31T08:00:00",{"rendered":170},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=46538&_wpnonce=d0b76defed&status=auto-draft&type=post","2022-10-17T14:09:07","2022-10-17T12:09:07","the-future-of-clinical-trials-artificial-patients-synthetic-data-and-real-time-analysis","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-clinical-trials-artificial-patients-synthetic-data-and-real-time-analysis",{"rendered":176},"The Future Of Clinical Trials: Artificial Patients, Synthetic Data And Real-Time Analysis",{"rendered":178,"protected":20},"\n\u003Cp>In this article, we summarise three concepts that are already\u002F will soon become familiar for everyone interested in the future of clinical trials. These are 1. the concept of the artificial patient, 2. using synthetic data and 3. real-time analyses.\u003C\u002Fp>\n\n\n\n\u003Cp>What connects the three is that all are potential tools to make clinical trials faster, cheaper and safer. That is so, in an ideal world. Because, as almost always, there is a catch, not even a small one. But more on it later. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The artificial patient\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Cstrong>What is it? \u003C\u002Fstrong>As of today, there is no final, widely accepted definition of what an artificial\u002Fvirtual\u002Fsynthetic patient is. A very detailed explanation about some (but not all) of the different definitions can be found \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC4318546\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">in this study\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>So let me phrase it simply what we mean by it in this analysis: \u003C\u002Fp>\n\n\n\n\u003Cblockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\u003Cp>an artificial patient is a set of data representing the desired human characteristics the best possible way that is based on large amounts of real patient data, without actually including any backtracable real-patient data. \u003C\u002Fp>\u003C\u002Fblockquote>\n\n\n\n\u003Cp>\u003Cstrong>Why is it? \u003C\u002Fstrong>Artificial patients can be the answer to more than one problems of modern medicine. One of them is patient privacy. With ever more machine learning and deep learning models being used, A.I. needs huge amounts of data to learn from. But providing a lot of real patient data is against their privacy rights, and we have seen ample examples of how bad an idea it is to allow random companies to access heaps of sensitive health data. On the other hand, taking a real-life dataset of existing humans, and generating a synthetic dataset that resembles the original in all important aspects (*more on it later) without actually including anything personal can be a solution.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>What is it good for?\u003C\u002Fstrong> Artificial patients can be used for a number of things, from medical education to clinical trials, this time we are only focusing on the latter. One day, virtual patients might become the go-to tools for\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>estimating efficiency and potential side effects of \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC7577280\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">promising drug molecules\u003C\u002Fa> or \u003Ca href=\"https:\u002F\u002Fbiblio.ugent.be\u002Fpublication\u002F8711822\u002Ffile\u002F8711823.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">optimising the use of existing ones\u003C\u002Fa>, \u003C\u002Fli>\u003Cli>to model the success rate of \u003Ca href=\"https:\u002F\u002Fwww.mdpi.com\u002F2077-0375\u002F12\u002F6\u002F548\" target=\"_blank\" rel=\"noreferrer noopener\">future medical devices\u003C\u002Fa> or \u003Ca href=\"https:\u002F\u002Fwww.medgadget.com\u002F2021\u002F06\u002Fin-silico-clinical-trial-replicates-results-of-traditional-trial.html\" target=\"_blank\" rel=\"noreferrer noopener\">treatment methods\u003C\u002Fa>, \u003C\u002Fli>\u003Cli>or, as the latest,\u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2022\u002F4\u002F28\u002F23044586\u002Fvr-chronic-pain-synthetic-clinical-trial-data\" target=\"_blank\" rel=\"noreferrer noopener\"> they can substitute the placebo control group\u003C\u002Fa> for clinical trials\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cp>As many hope, one day artificial patients may be able to completely substitute humans and animals in clinical trials, most likely with animals being the first. \u003C\u002Fp>\n\n\n\n\u003Cp>While using artificial patients for drug development or medical device development is a promising field, there is a long way to go until the models can reach the required complexity while being truly representative of the human population.\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\u002F2019\u002F06\u002F093_will_we_born_in_2050-768x432.png\" alt=\"artificial womb\" class=\"wp-image-24181\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F06\u002F093_will_we_born_in_2050-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F06\u002F093_will_we_born_in_2050-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F06\u002F093_will_we_born_in_2050-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F06\u002F093_will_we_born_in_2050-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F06\u002F093_will_we_born_in_2050.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>On the other hand, artificial patients as the placebo control group have arrived. AppliedVR \u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2022\u002F4\u002F28\u002F23044586\u002Fvr-chronic-pain-synthetic-clinical-trial-data\" target=\"_blank\" rel=\"noreferrer noopener\">recently conducted a trial\u003C\u002Fa> for VR treatment for chronic back pain patients. And instead of recruiting patients to sign up for the trials to not receive the treatment (being the control group), they decided to turn to an existing database of chronic pain patients, provided by healthcare data company Komodo Health. \u003C\u002Fp>\n\n\n\n\u003Cp>Using real-world data as a patient group in a trial, often known as a synthetic control arm, can make research trials more efficient — companies don’t have to enrol as many people in clinical trials and can guarantee that those who apply will indeed receive the treatment. \u003C\u002Fp>\n\n\n\n\u003Cp>Synthetic control groups can also improve equity in clinical research. “That allows us to go look at all those different subpopulations and underrepresented patient populations to see if they have different outcomes,” Web Sun, president and co-founder of Komodo Health says. \u003C\u002Fp>\n\n\n\n\u003Cp>Another interesting example was this\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.medgadget.com\u002F2021\u002F06\u002Fin-silico-clinical-trial-replicates-results-of-traditional-trial.html\" target=\"_blank\"> virtual trial\u003C\u002Fa> (or in-silico trial) carried out to predict the efficiency of using flow diverters for brain aneurysms. Researchers created 82 virtual patients based on data of real patients from previous flow diverter trials. The experiment projected an 82.9% success rate for the use of diverters, pretty close to the results of three real-world flow diverter trials that had 86.8%, 74.8% and 76.8% success rates respectively.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Synthetic data\u003C\u002Fh2>\n\n\n\n\u003Cp>If you felt like your head started spinning from dealing with the concept of the artificial patient, behold, synthetic data is probably an even wilder ride. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>What is it?\u003C\u002Fstrong> The definition is simpler this time: synthetic data is the use of A.I. to create datasets that mimic the real world.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Why is it?\u003C\u002Fstrong> Because we 1. don’t have enough real-world data or 2. don’t want to use real-world (sensitive) data.\u003Cbr>\u003Cstrong>What is it good for?\u003C\u002Fstrong> Feeding any algorithm that needs massive amounts of data to learn and either develop new prediction capabilities or recognise patterns. Synthetic data is widely used in a number of industries and segments, not just in medicine, but also in self-driving vehicles, security, robotics, fraud protection, insurance models, military and so on.\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\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-768x432.png\" alt=\"health data\" class=\"wp-image-24937\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health-512x288.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F110_All-the-things-we-can-measure-in-digital-health.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Artificial intelligence has earned its place \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fsynthetic-data-in-healthcare-will-smarter-data-bring-the-a-i-revolution-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">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>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\" target=\"_blank\" rel=\"noreferrer noopener\">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\">f\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffederated-learning-can-protect-patients-data-in-hospitals\" target=\"_blank\" rel=\"noreferrer noopener\">e\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ffederated-learning-can-protect-patients-data-in-hospitals\">derated 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’s when synthetic data comes in. 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\u003Cp>Using 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\" target=\"_blank\" rel=\"noreferrer noopener\"> previous algorithms have failed\u003C\u002Fa> to be able to do so.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">But not everything is just sunshine and sandy beaches\u003C\u002Fh2>\n\n\n\n\u003Cp>This \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fiai.tv\u002Farticles\u002Fwe-should-all-be-worried-about-synthetic-data-auid-2138&utm_source=reddit&_auid=2020\" target=\"_blank\">insightful analysis\u003C\u002Fa> not only explains how and why synthetic data is used, but also why we should be scared of it. In short: any dataset we create will be imperfect to some extent. It will contain biases we are not aware of. It will not include important variables we either overlooked or are not aware of their importance. Even, in the best of cases, it will be like a snapshot of a given moment of a given situation. \u003C\u002Fp>\n\n\n\n\u003Cp>If we let machine learning and deep learning algorithms develop on these synthetic, imperfect datasets, chances are they will come to conclusions that are more or less false in the real world. \u003C\u002Fp>\n\n\n\n\u003Cp>And the reason why this is worrying is the speed at which the use of synthetic data is spreading. Gartner predicts that by 2024 some 60% of all data used for AI will be synthetic. And not just in medicine. \u003C\u002Fp>\n\n\n\n\u003Cp>Synthetic data is cheap and easy to come by, much easier and cheaper than collecting huge amounts of messy real-world data. What happens if decisions affecting large groups of people or whole societies will be made based on it? \u003C\u002Fp>\n\n\n\n\u003Cp>It is especially worrying as the world already faces challenges regarding “truth”. Introducing alternative truths based on ‘data’ to back decisions affecting societies – like healthcare funding, insurance models and so on – can have devastating consequences.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Real-time \u002F decentralised clinical trials\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Cstrong>What is it?\u003C\u002Fstrong> The use of electronic health data\u002Frecords\u002Fdevices to carry out clinical trials in near real-time with patients not needed to be present on site.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Why is it? \u003C\u002Fstrong>Real-time trials offer faster results and the possibility of participants to directly connect to other patients, share their experiences and get access to results. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>What is it good for?\u003C\u002Fstrong> More committed participants and faster results. \u003C\u002Fp>\n\n\n\n\u003Cp>We have seen a few good examples in recent months.\u003C\u002Fp>\n\n\n\n\u003Cp>One is that of \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.mobihealthnews.com\u002Fnews\u002Froyal-philips-rolls-out-home-ecg-system-decentralized-clinical-trials\" target=\"_blank\">Royal-Philips rolling out a new at-home ECG system\u003C\u002Fa> for decentralised clinical trial use. The company is pitching this new technology as a way for clinical trial participants to record ECG data without travelling to a clinical site or requiring an in-home clinician. Data of trial participants can be transmitted near real-time to the cloud servers for analysis. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"494\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2016\u002F09\u002Fclinical-trials-768x494.jpg\" alt=\"Clinical Trials\" class=\"wp-image-14141\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2016\u002F09\u002Fclinical-trials-768x494.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2016\u002F09\u002Fclinical-trials-512x330.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2016\u002F09\u002Fclinical-trials-389x250.jpg 389w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2016\u002F09\u002Fclinical-trials.jpg 870w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>A number of digital health companies are designing tools to enable decentralised trials. In September, digital wound-care company \u003Ca href=\"https:\u002F\u002Fwww.mobihealthnews.com\u002Fnews\u002Fswift-medicals-new-imaging-platform-expands-digital-wound-care-company-decentralized-trials\" target=\"_blank\" rel=\"noreferrer noopener\">Swift Medical\u003C\u002Fa> launched a new digital-imaging platform designed to support decentralised clinical trials. The technology was designed to aid in large-scale image collection and management in order for researchers to monitor the impact of medical interventions at various sites or at home.\u003C\u002Fp>\n\n\n\n\u003Cp>Deploying such advanced technologies in clinical trials will require pharmaceutical and biotech companies to commit not only financially but also to the idea that technologies can significantly contribute to clinical trials, making drugs cheaper, making the process faster and much more importantly, making the lives of patients participating in them more comfortable.\u003C\u002Fp>\n",{"rendered":180,"protected":20},"\u003Cp>Three important concepts explained that are expected to make future clinical trials faster, safer and cheaper, without real humans and animals.\u003C\u002Fp>\n",24545,{"_acf_changed":20,"footnotes":27},[31,184,32,185,186,187],6261,798,491,521,[189,190,191,192,193,194,195,196,197,198],7580,566,636,671,7477,7577,1530,7578,7579,306,[200],953,[],[203,204,205,206,207,208],1631,1635,1693,1803,1807,1621,[210,14,52,53,54,55,56,57,211,58,212,213,214,215,216,217,218,219,220,221,222,223,224,225],"post-46538","category-forecast","category-digital-health-research","category-empowered-patients","category-future-medicine","tag-real-time-analysis","tag-clinical-trials","tag-deep-learning","tag-machine-learning","tag-synthetic-data","tag-artificial-patient","tag-drug-design","tag-virtual-patient","tag-synthetic-patient","tag-medical-device","project_category-researchers",{"id":181,"alt_text":227,"caption":27,"description":228,"media_type":68,"media_details":229,"post":260,"source_url":261},"in silico trials, synthetic data, artificial patient, TMF","synthetic data, artificial patient, 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