[{"data":1,"prerenderedAt":394},["ShallowReactive",2],{"slug-medpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor":3},{"post":4,"relatedPosts":170,"relatedBooks":298},{"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":32,"project_category":43,"contact_email_category":45,"yst_prominent_words":46,"class_list":53,"better_featured_image":72,"acf":104,"yoast_meta":114,"_links":117},48665,"2023-01-17T10:00:00","2023-01-17T09:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=48665&_wpnonce=dff5872b54&status=auto-draft&type=post","2023-01-17T07:42:35","2023-01-17T06:42:35","medpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fmedpalm-new-ai-medical-chatbots-will-soon-be-better-than-waiting-for-a-doctor",{"rendered":17},"MedPaLM: New AI Medical Chatbots Will Soon Be Better Than Waiting For A Doctor",{"rendered":19,"protected":20},"\n\u003Cp>Large language models (LLMs), these excitingly versatile algorithms became a topic of general conversation in December 2022, when OpenAI released its GPT3 agent, also known as ChatGPT. LLMs are developed to carry on conversations in human-like ways, they are designed to understand complex queries and respond in a nuanced manner. We introduced potential medical use cases \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002F6-potential-medical-use-cases-for-chatgpt\" target=\"_blank\" rel=\"noreferrer noopener\">in this article\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>By now we all have a track record with some kind of a chatbot – if nothing else, a not-very-bright algorithm at a service provider. These interactions rarely left anyone particularly impressed, they sometimes contribute to solving our problems, but more often than not just result in a frustrated user leaving with a promise of contact from a human support staff member that may or may never happen. \u003C\u002Fp>\n\n\n\n\u003Cp>Large language models undoubtedly have changed this field forever, they are capable of such high-quality assistance that was never seen earlier. Only a few short weeks after the release of ChatGPT, Google\u002FDeepMind announced \u003Ca href=\"https:\u002F\u002Fpharmaphorum.com\u002Fnews\u002Fgoogle-and-deepmind-share-work-on-medical-chatbot-med-palm\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">the release of MedPaLM\u003C\u002Fa>, a large language model specifically designed to answer healthcare-related questions, based on their 540-billion parameter PaLM model.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"351\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002FMedpalm2-768x351.jpg\" alt=\"Medpalm google deepmind large languae model\" class=\"wp-image-48673\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002FMedpalm2-768x351.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002FMedpalm2.jpg 988w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>This model was trained on six existing medical Q&A datasets (NedQA, MedMCQA, PubMedQA, LiveQA, MedicationQA, and MMLU), and the developer teams also created their own HealthSearchQA, using questions about medical conditions and the associated symptoms.\u003C\u002Fp>\n\n\n\n\u003Cp>At the moment MedPaLM can’t be tested by the general public, but you can read the \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2212.13138.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">researcher’s paper here\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">It “performs encouragingly but remains inferior to clinicians”\u003C\u002Fh3>\n\n\n\n\u003Cp>The document lists a number of possible medical applications, including knowledge retrieval, clinical decision support, summarisation of key findings in studies, and triaging patients’ primary care concerns among others, but also noted that MedPaLM “performs encouragingly, but remains inferior to clinicians.”\u003C\u002Fp>\n\n\n\n\u003Cp>The attached diagrams show that MedPaLM was still underperforming human clinicians in several areas: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>incorrect retrieval of information was 16.9% for Med-PaLM, which compares to 3.6% of clinicians\u003C\u002Fli>\n\n\n\n\u003Cli>incorrect reasoning was seen in 10.1% of the MedPaLM answers and in 2.1% of clinician answers\u003C\u002Fli>\n\n\n\n\u003Cli>incorrect comprehension happened in 18.7% of cases for the algorithm and in 2.2% for the clinicians\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"533\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Fmedpalm-768x533.jpg\" alt=\"\" class=\"wp-image-48669\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Fmedpalm-768x533.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Fmedpalm.jpg 995w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Some examples of answers crafted by MedPaLM\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>\u003Cstrong>Large language models may easily be the best option we’ll have for medical consultations\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Although the model is obviously not perfect, it does significantly better than any previous algorithms, and the field is improving fast. The LLM-based chatbot algorithms provide a never-before-seen quality of human-AI interaction.\u003C\u002Fp>\n\n\n\n\u003Cp>This is what I think will happen: as these models get better and better, the risk of missing care due to capacity shortages in healthcare will soon outweigh the risk of the algorithms being wrong. We will be better off familiarising ourselves with communicating with such an LLM algorithm – purely because long waiting for medical answers due to the lack of healthcare personnel will pose a higher threat. \u003C\u002Fp>\n\n\n\n\u003Cp>Live consultation with a doctor will become a luxury in the 21st century, and any solution addressing this issue (from asynchronous telemedicine to medical chatbots) will actually improve our health prospects.\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>As these models get better and better, the risk of missing care due to capacity shortages in healthcare will soon outweigh the risk of the algorithms being wrong. \u003C\u002Fp>\n",6,48671,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31],504,[33,34,35,36,37,38,39,40,41,42],734,7739,7741,7743,7745,7747,7749,7687,7691,7737,[44],950,[],[47,48,49,50,51,52],1723,2313,2649,2689,2693,2705,[54,14,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71],"post-48665","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-chatbots","tag-ai-chatbots","tag-large-language-models","tag-chat-gpt","tag-medpalm","tag-openai","tag-deep-mind","tag-ai-text-generator","tag-ai-in-heaalthcare","tag-medical-chatbots","project_category-medical-professionals",{"id":24,"alt_text":73,"caption":27,"description":27,"media_type":74,"media_details":75,"post":5,"source_url":103},"medical chatbot AI algorithm person man phone 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New Chatbots Will Soon Be Better Than Waiting For A Doctor","As models like MedPaLM get better, the risk of missing care due to capacity shortages in healthcare will outweigh the risk of the algorithms being wrong.",{"self":118,"collection":124,"about":127,"author":130,"replies":133,"version-history":136,"predecessor-version":140,"wp:featuredmedia":144,"wp:attachment":147,"wp:term":150,"curies":166},[119],{"href":120,"targetHints":121},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F48665",{"allow":122},[123],"GET",[125],{"href":126},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[128],{"href":129},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[131],{"embeddable":26,"href":132},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[134],{"embeddable":26,"href":135},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=48665",[137],{"count":138,"href":139},7,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F48665\u002Frevisions",[141],{"id":142,"href":143},48723,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F48665\u002Frevisions\u002F48723",[145],{"embeddable":26,"href":146},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F48671",[148],{"href":149},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=48665",[151,154,157,160,163],{"taxonomy":152,"embeddable":26,"href":153},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=48665",{"taxonomy":155,"embeddable":26,"href":156},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=48665",{"taxonomy":158,"embeddable":26,"href":159},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=48665",{"taxonomy":161,"embeddable":26,"href":162},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=48665",{"taxonomy":164,"embeddable":26,"href":165},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=48665",[167],{"name":168,"href":169,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[171],{"id":113,"date":172,"date_gmt":173,"guid":174,"modified":176,"modified_gmt":177,"slug":178,"status":13,"type":14,"link":179,"title":180,"content":182,"excerpt":184,"author":23,"featured_media":186,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":187,"categories":188,"tags":190,"project_category":197,"contact_email_category":198,"yst_prominent_words":199,"class_list":202,"better_featured_image":211,"acf":245,"yoast_meta":253,"_links":256},"2022-11-02T10:00:00","2022-11-02T09:00:00",{"rendered":175},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=47785&_wpnonce=37f261ba13&status=auto-draft&type=post","2022-11-02T07:25:15","2022-11-02T06:25:15","generative-adversarial-networks-how-can-ai-learn-so-much-while-its-iq-remains-zero","https:\u002F\u002Fmedicalfuturist.com\u002Fgenerative-adversarial-networks-how-can-ai-learn-so-much-while-its-iq-remains-zero",{"rendered":181},"Generative Adversarial Networks: How Can AI Learn So Much While Its IQ Remains Zero?",{"rendered":183,"protected":20},"\n\u003Cp>A short while ago we wrote about \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhere-is-how-you-get-friendly-with-a-i-before-it-gets-to-the-office\">why it is a good idea to get friendly with AI\u003C\u002Fa> before it arrives in your everyday work environment. We introduced the text-to-art algorithm Midjourney – as an easy and entertaining partner for this venture.\u003C\u002Fp>\n\n\n\n\u003Cp>But how do these algorithms work? How can they translate our words (Superman and Wonderwoman in Starbucks) into (more or less) fitting images? And how is it possible that while these models get better and better, their IQ remains 0?\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image is-style-default\">\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FSuperman-and-Wonderwoman-in-Starbucks.png\" alt=\"\" class=\"wp-image-47789\" width=\"639\" height=\"639\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FSuperman-and-Wonderwoman-in-Starbucks.png 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FSuperman-and-Wonderwoman-in-Starbucks-150x150.png 150w\" sizes=\"auto, (max-width: 639px) 100vw, 639px\" \u002F>\u003Cfigcaption>Superman and Wonderwoman in Starbucks – by Midjourney\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>Welcome to the wonderful world of Generative Adversarial Networks or GANs for short. These are a type of A.I. (a neural network to be precise) that can generate data from scratch. And although this topic is quite complicated, it is easy to understand the basic principle of how they learn. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The famous case of the forger and the art detective\u003C\u002Fh2>\n\n\n\n\u003Cp>Imagine a Talented Youngster who decides to make his fortune by forging Picasso. He has a severe disadvantage though: although he has read about the painter, he has never seen any of his paintings. On the upside, he has an excellent style guide that includes the important characteristics of the painter’s works, like the colours he often used, his typical brushstroke techniques and the topic of his paintings. And he has a superpower: he paints with incredible speed, generating tons of new pictures every day. \u003C\u002Fp>\n\n\n\n\u003Cp>Then there is the Art Detective, who knows a good deal about Picasso’s paintings, as he examined all of them in great detail during his training.\u003C\u002Fp>\n\n\n\n\u003Cp>So how does our young forger get to the point when he can produce a painting to be auctioned as a genuine Picasso? He goes for trial and error.\u003C\u002Fp>\n\n\n\n\u003Cp>He starts painting completely random things using the info from his Picasso style guide, and submits all his work to the art detective, asking for a judgement if the painting is a genuine Picasso. He carefully watches the reaction. Most of the time the detective won’t even cast a longer look at the painting before rejecting it. \u003C\u002Fp>\n\n\n\n\u003Cp>When this happens, our forger gets the feedback: what he painted was not plausible. \u003C\u002Fp>\n\n\n\n\u003Cp>But every now and then the detective takes a few seconds before saying no, probably even taking out his magnifying glasses to examine some details. And our painter watches and learns, generating better and better images in the style of Picasso.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-resized is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FUpscaled-Picasso-768x439.png\" alt=\"Midjourney text to art algorithm picture Picasso\" class=\"wp-image-47787\" width=\"768\" height=\"439\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FUpscaled-Picasso-768x439.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FUpscaled-Picasso.png 1280w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption>Midjourney’s take on “A Picasso painting of a woman”\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Through this constant cycle of trial and feedback, the painter gets better and better, and eventually gets to a point when he is able to create a plausible painting in the style of Picasso. \u003C\u002Fp>\n\n\n\n\u003Cp>Both the painter and the detective need to learn during this process, as the forged Picassos get more convincing, the detective needs to improve to catch them. The better the detective gets, the more the painter needs to improve to trick him. And so on, and so on. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">The generator and the discriminator\u003C\u002Fh2>\n\n\n\n\u003Cp>GAN networks contain two algorithms, called the generator and the discriminator. The generator is our painter, creating outputs with the goal of fooling the discriminator. \u003C\u002Fp>\n\n\n\n\u003Cp>The discriminator is our detective. It was trained on real datasets, and its job is to tell the generator if the output it created is valid or not. \u003C\u002Fp>\n\n\n\n\u003Cp>They play a zero-sum game: if the generator fools the discriminator, it wins. If the discriminator catches the output as fake, it wins. They teach each other in a process called unsupervised learning. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Why is their IQ still zero?\u003C\u002Fh2>\n\n\n\n\u003Cp>As the above images – created by Midjourney again – suggest, these algorithms have advanced a lot. The first take on a woman in the style of Picasso is a pretty good one. How come they are said to still not have any intelligence in the meaning we think of intelligence? \u003C\u002Fp>\n\n\n\n\u003Cp>Playing with the algorithm helps you to understand this matter. Midjourney has indeed learned a lot about the various parameters of images flagged as “woman”. However, this learning is distinctly different from the mental construct we, humans have when thinking about a woman. \u003C\u002Fp>\n\n\n\n\u003Cp>From Midjourney’s point of view, a woman is a set of pixels distributed in a form that passes the discriminator’s judgement. Where we see long hair or boobs, Midjourney sees pixels arranged in a format that passes the test.\u003C\u002Fp>\n\n\n\n\u003Cp>The more you experiment with it, the clearer it becomes that although it is able to make a picture of a woman, it has absolutely no idea of \u003Cem>what a woman is\u003C\u002Fem>. It can paint a picture of a father and a son but has no idea what being a father and\u002For a son means and about the relationship between them.\u003C\u002Fp>\n\n\n\n\u003Cp>This lack of conceptual understanding is pretty easy to catch in the Superman and Wonderwoman image above. The algorithm was able to identify visual clues of both characters but mixed and matched them in a random pattern. Midjourney kind of understands that these are important details, but has no grasp on who Superman or Wonderwoman is, and what they should do in Starbucks. Although the coffee part is ok.\u003C\u002Fp>\n\n\n\n\u003Cp>Experiencing this gap between being able to picture a woman and understanding what a woman is will help you grasp why you shouldn’t worry A.I. will take your job. (As of yet. Developing properly functioning artificial general intelligence and artificial superintelligence will change this forever, and then we might find ourselves in a scary movie. We will let you know in time.)\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">So why is it good for healthcare?\u003C\u002Fh2>\n\n\n\n\u003Cp>GAN networks, despite their zero IQ, can serve well in the future of medicine. Here are two examples of where they will deliver in the near future.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>1. They can create endless amounts of synthetic patients data and datasets for other algorithms\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>Based on the above-discussed principles, these algorithms \u003Ca href=\"https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fpmc\u002Farticles\u002FPMC9345230\u002F\">can be trained to generate “patient data”\u003C\u002Fa> that passes the discriminator’s judgement. Based on huge real datasets they can create synthetic patient data that resembles the real thing in all important characteristics but carries no privacy issues. (We wrote about the potential, the limitations and possible faults\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-clinical-trials-artificial-patients-synthetic-data-and-real-time-analysis\"> in this article\u003C\u002Fa>). Synthetic patient data can be used for a number of things, including clinical trials and medical education.\u003C\u002Fp>\n\n\n\n\u003Cp>Radiology is probably THE medical specialty that benefits the most from A.I. An algorithm that is capable of going through thousands of images a day flagging the ones with suspected tumours is huge. But to have an algorithm like this, someone has to teach it. Which requires radiologists to mark each and every tumour pixel in each and every image in the training dataset, so A.I. can learn what to look for. This represents a very real barrier to creating sufficiently large samples of data. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs44163-021-00006-0\">GAN can bridge this gap\u003C\u002Fa>: it can be trained to create “valid” medical images with the tumour cells marked, so the other algorithms will have enough data to learn from. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>2. GAN can create a virtual workforce for healthcare (too) \u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cp>This is an uncanny example. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.synthesia.io\u002Fabout\" target=\"_blank\">Synthesia \u003C\u002Fa>generates training and sales videos featuring photorealistic, synthetic talking heads that read personalised scripts in any of 34 languages, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.wired.com\u002Fstory\u002Fcovid-drives-real-businesses-deepfake-technology\u002F\" target=\"_blank\">Wired reported a while ago\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.synthesia.io\u002Fpost\u002Fthe-future-of-synthetic-media\" target=\"_blank\">Synthetic media\u003C\u002Fa> enables us to create pictures based on text prompts, realistic talking-head videos from typing in text, and get high-quality text by simply telling the A.I. what we want to be written and how. From here, there is only one more step to use these networks to generate new colleagues who are ready to take over some tasks. \u003C\u002Fp>\n\n\n\n\u003Cp>These virtual employees are outfitted with programmed personalities and generated smiles, and it’s getting harder to differentiate them from real people. Don’t get surprised if you start seeing these virtual employees in the administration and billing departments of hospitals; or as the representatives talking with you from your health insurance company soon. \u003C\u002Fp>\n",{"rendered":185,"protected":20},"\u003Cp>Generative Adversarial Networks are very smart, but they have no IQ at all. It is easy to understand how they work if we imagine a forger and a detective.\u003C\u002Fp>\n",47791,{"_acf_changed":20,"footnotes":27},[189,31],7079,[191,192,193,194,195,196],636,7479,7683,134,137,144,[44],[],[200,201],1693,1807,[203,14,55,56,57,58,59,204,60,205,206,207,208,209,210,71],"post-47785","category-tmf","tag-deep-learning","tag-gan","tag-generative-adversarial-networks","tag-ai","tag-algorithm","tag-artificial-intelligence",{"id":186,"alt_text":212,"caption":27,"description":27,"media_type":74,"media_details":213,"post":113,"source_url":244},"Generative Adversarial Networks GAN AI algorithm",{"width":214,"height":215,"file":216,"sizes":217,"image_meta":243},1920,1080,"2022\u002F10\u002Ftmf_article_311-01.png",{"medium":218,"large":223,"thumbnail":228,"medium_large":232,"1536x1536":233,"2048x2048":238},{"file":219,"width":220,"height":221,"mime-type":85,"source_url":222},"tmf_article_311-01-370x208.png","370","208","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01-370x208.png",{"file":224,"width":225,"height":226,"mime-type":85,"source_url":227},"tmf_article_311-01-768x432.png","768","432","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01-768x432.png",{"file":229,"width":230,"height":230,"mime-type":85,"source_url":231},"tmf_article_311-01-150x150.png","150","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01-150x150.png",{"file":224,"width":225,"height":226,"mime-type":85,"source_url":227},{"file":234,"width":235,"height":236,"mime-type":85,"source_url":237},"tmf_article_311-01-1536x864.png","1536","864","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01-1536x864.png",{"file":239,"width":240,"height":241,"mime-type":85,"source_url":242},"tmf_article_311-01-2048x1152.png","2048","1152","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01-2048x1152.png",{"aperture":101,"credit":27,"camera":27,"caption":27,"created_timestamp":101,"copyright":27,"focal_length":101,"iso":101,"shutter_speed":101,"title":27,"orientation":101},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002Ftmf_article_311-01.png",{"cta_type":105,"cta_color":27,"related_books":246,"related_posts_footer":249,"related_posts":20,"subtitle":27},[247,248,107],30419,47427,[250,251,252],39279,46538,47495,{"yoast_wpseo_title":254,"yoast_wpseo_metadesc":255,"yoast_wpseo_canonical":179},"Generative Adversarial Networks: How AI Can Be Smart With No IQ At All","Generative Adversarial Networks are very smart, but they have no IQ at all. It is easy to understand how they work if we imagine a forger and a detective.",{"self":257,"collection":262,"about":264,"author":266,"replies":268,"version-history":271,"predecessor-version":275,"wp:featuredmedia":279,"wp:attachment":282,"wp:term":285,"curies":296},[258],{"href":259,"targetHints":260},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47785",{"allow":261},[123],[263],{"href":126},[265],{"href":129},[267],{"embeddable":26,"href":132},[269],{"embeddable":26,"href":270},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=47785",[272],{"count":273,"href":274},10,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47785\u002Frevisions",[276],{"id":277,"href":278},47821,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F47785\u002Frevisions\u002F47821",[280],{"embeddable":26,"href":281},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F47791",[283],{"href":284},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=47785",[286,288,290,292,294],{"taxonomy":152,"embeddable":26,"href":287},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=47785",{"taxonomy":155,"embeddable":26,"href":289},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=47785",{"taxonomy":158,"embeddable":26,"href":291},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=47785",{"taxonomy":161,"embeddable":26,"href":293},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=47785",{"taxonomy":164,"embeddable":26,"href":295},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=47785",[297],{"name":168,"href":169,"templated":26},[299],{"id":109,"date":300,"date_gmt":301,"guid":302,"modified":304,"modified_gmt":305,"slug":306,"status":13,"type":307,"link":308,"title":309,"content":311,"excerpt":313,"author":273,"featured_media":315,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":316,"class_list":318,"better_featured_image":321,"acf":339,"yoast_meta":363,"_links":365},"2019-09-06T21:56:27","2019-09-06T19:56:27",{"rendered":303},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=24759","2023-03-12T18:06:35","2023-03-12T17:06:35","the-technological-future-of-medical-specialties","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fthe-technological-future-of-medical-specialties\u002F",{"rendered":310},"The Technological Future of Medical Specialties",{"rendered":312,"protected":20},"\n\u003Cp>In this e-book we specify in detail how the appearance of artificial intelligence, sensors, wearables, VR\u002FAR or robots affect each medical specialty in order to be able to discern what skills physicians will need in the future. We aim to show how physicians of the various professions can successfully prepare for the sweeping changes coming with the waves of technology. \u003C\u002Fp>\n",{"rendered":314,"protected":20},"\u003Cp>In this e-book we specify in detail how the appearance of artificial intelligence, sensors, wearables, VR\u002FAR or robots affect each medical specialty in order to […]\u003C\u002Fp>\n",49971,[317],2015,[319,307,320,56,58,59],"post-24759","type-book",{"id":315,"alt_text":27,"caption":27,"description":27,"media_type":74,"media_details":322,"post":109,"source_url":338},{"width":323,"height":324,"file":325,"filesize":326,"sizes":327,"image_meta":337},320,414,"2019\u002F09\u002Ffuture-of-medical-specialties.png",24785,{"medium":328,"thumbnail":333},{"file":329,"width":330,"height":221,"mime-type":85,"filesize":331,"source_url":332},"future-of-medical-specialties-320x208.png","320","52681","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties-320x208.png",{"file":334,"width":230,"height":230,"mime-type":85,"filesize":335,"source_url":336},"future-of-medical-specialties-150x150.png","26567","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties-150x150.png",{"aperture":101,"credit":27,"camera":27,"caption":27,"created_timestamp":101,"copyright":27,"focal_length":101,"iso":101,"shutter_speed":101,"title":27,"orientation":101},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002Ffuture-of-medical-specialties.png",{"leanpub_url":340,"buy_button_text":341,"preview":342},"https:\u002F\u002Fleanpub.com\u002Ffuture-of-medical-specialties","Get it on Leanpub",[343,345,347,349,351,353,355,357,359,361],{"image":344},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-01.png",{"image":346},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-02.png",{"image":348},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-03.png",{"image":350},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-04.png",{"image":352},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-05.png",{"image":354},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-06.png",{"image":356},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-07.png",{"image":358},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-08.png",{"image":360},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-09.png",{"image":362},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002FThe-Technological-Future-of-Medical-Specialties-2021-Preview-10.png",{"yoast_wpseo_title":364,"yoast_wpseo_metadesc":27,"yoast_wpseo_canonical":308},"The Technological Future of Medical Specialties - The Medical Futurist",{"self":366,"collection":371,"about":374,"author":377,"replies":380,"wp:featuredmedia":383,"wp:attachment":386,"wp:term":389,"curies":392},[367],{"href":368,"targetHints":369},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F24759",{"allow":370},[123],[372],{"href":373},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[375],{"href":376},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[378],{"embeddable":26,"href":379},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F10",[381],{"embeddable":26,"href":382},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=24759",[384],{"embeddable":26,"href":385},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49971",[387],{"href":388},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=24759",[390],{"taxonomy":164,"embeddable":26,"href":391},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=24759",[393],{"name":168,"href":169,"templated":26},1786432668271]