[{"data":1,"prerenderedAt":373},["ShallowReactive",2],{"slug-using-chatgpt-offline-the-emergence-of-small-language-models":3},{"post":4,"relatedPosts":172,"relatedBooks":293},{"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":36,"contact_email_category":38,"yst_prominent_words":39,"class_list":45,"better_featured_image":57,"acf":100,"yoast_meta":117,"_links":119},55115,"2026-03-02T09:06:27","2026-03-02T08:06:27",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=55115&_wpnonce=45ed6c25a3&status=auto-draft&type=post","2026-03-02T09:06:28","2026-03-02T08:06:28","using-chatgpt-offline-the-emergence-of-small-language-models","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fusing-chatgpt-offline-the-emergence-of-small-language-models",{"rendered":17},"Using ChatGPT Offline: How Small Language Models Can Aid Healthcare Professionals",{"rendered":19,"protected":20},"\n\u003Cp>By now, you might have come across the term large language models (LLMs), which is \u003Ca href=\"https:\u002F\u002Fblog.google\u002Finside-google\u002Fgooglers\u002Fask-a-techspert\u002Fwhat-is-generative-ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">a type of generative artificial intelligence\u003C\u002Fa> (GenAI). If not, you have likely encountered \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fgenerative-ai-explained-its-impact-and-future-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">GenAI applications\u003C\u002Fa> that are based on LLMs. This includes the likes of ChatGPT, Google Bard and Microsoft Copilot. While such models have proved useful, in the healthcare setting, they come with \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-and-how-to-regulate-chatgpt-like-large-language-models-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">new sets\u003C\u002Fa> of regulatory, ethical and privacy concerns.\u003C\u002Fp>\n\n\n\n\u003Cp>Recently, another type of language model has been \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnews.microsoft.com\u002Fthree-big-ai-trends-to-watch-in-2024\u002F\" target=\"_blank\">gaining attention\u003C\u002Fa> in the GenAI field: the small language model (SLM). It even holds the promise of addressing some of the challenges with integrating LLMs in healthcare. In this article, we will introduce SLMs, compare them to LLMs and explore their healthcare potential.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What are SLMs?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>Like LLMs, SLMs are a type of GenAI and \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fsmall-language-models-what-why-matter-vishnuvaradhan-v-0qypc\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">operate in similar ways\u003C\u002Fa>. This means that they rely on neural networks to learn patterns from language in text to produce new text of their own. \u003C\u002Fp>\n\n\n\n\u003Cp>SLMs are termed as “small” as they are trained \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fsmall-language-models-what-why-matter-vishnuvaradhan-v-0qypc\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">on relatively small\u003C\u002Fa> amounts of data and have a relatively small number of parameters. Parameters here \u003Ca href=\"https:\u002F\u002Fblog.wordbot.io\u002Fai-artificial-intelligence\u002Fnlp-models-the-importance-of-parameters\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">refer to\u003C\u002Fa> variables that define the model’s structure and behavior.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F07\u002Ftmf_article_380-768x432.png\" alt=\"\" class=\"wp-image-51765\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F07\u002Ftmf_article_380-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F07\u002Ftmf_article_380-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F07\u002Ftmf_article_380-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F07\u002Ftmf_article_380.png 1980w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Emphasis should be paid on \u003Cstrong>\u003Cem>relatively\u003C\u002Fem> \u003C\u002Fstrong>as SLMs still involve \u003Ca href=\"https:\u002F\u002Fwww.theregister.com\u002F2023\u002F11\u002F13\u002Fgenerative_ai_its_not_just\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">millions or even billions of parameters\u003C\u002Fa>. However, this range of parameters in SLM is “small” in comparison to LLMs and we’ll consider the differences between these models in the next section.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>SLM and LLM: what’s the difference?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>While there is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fsmall-language-models-what-why-matter-vishnuvaradhan-v-0qypc\u002F\" target=\"_blank\">no clear threshold\u003C\u002Fa> for SLMs, they usually \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theregister.com\u002F2023\u002F11\u002F13\u002Fgenerative_ai_its_not_just\u002F\" target=\"_blank\">tend to have between\u003C\u002Fa> a hundred million to tens of billions of parameters. While still large numbers, this range is small compared to the number of parameters LLMs possess which can reach hundreds of billions. Consider OpenAI’s GPT-3: this LLM \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fsmall-language-models-what-why-matter-vishnuvaradhan-v-0qypc\u002F\" target=\"_blank\">has 175 billion parameters\u003C\u002Fa>, and GPT-4 is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theinformation.com\u002Farticles\u002Fthe-rise-of-small-language-models-and-reinforcement-learning\" target=\"_blank\">believed to have\u003C\u002Fa> about a trillion parameters. In comparison, Microsoft \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fresearch\u002Fblog\u002Fphi-2-the-surprising-power-of-small-language-models\u002F\" target=\"_blank\">recently introduced Phi-2\u003C\u002Fa>, an SLM developed by the company’s researchers with \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fresearch\u002Fblog\u002Fphi-2-the-surprising-power-of-small-language-models\u002F\" target=\"_blank\">2.7 billion parameters\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>This difference in architecture is reflected in the resources required to run the different types of models. LLMs require \u003Ca href=\"https:\u002F\u002Fventurebeat.com\u002Fai\u002Fgenerative-ai-and-the-big-buzz-about-small-language-models\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">significant computing resources\u003C\u002Fa> from servers to storage. Such needs trickle down to the huge costs associated with running such models; and are thus not accessible or even feasible to every organisation. In comparison, SLMs can be small enough to run \u003Ca href=\"https:\u002F\u002Fnews.microsoft.com\u002Fthree-big-ai-trends-to-watch-in-2024\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">offline on a phone\u003C\u002Fa> while bearing significantly less operational costs.\u003C\u002Fp>\n\n\n\n\u003Cp>“Small language models can make AI more accessible due to their size and affordability,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnews.microsoft.com\u002Fthree-big-ai-trends-to-watch-in-2024\u002F\" target=\"_blank\">says Sebastien Bubeck\u003C\u002Fa>, who leads the Machine Learning Foundations group at Microsoft Research. “At the same time, we’re discovering new ways to make them as powerful as large language models.”\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"439\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-VKCtW6J0oTWs3Xy8XRa19htk-768x439.jpg\" alt=\"\" class=\"wp-image-55157\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-VKCtW6J0oTWs3Xy8XRa19htk-768x439.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-VKCtW6J0oTWs3Xy8XRa19htk-1536x878.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ffile-VKCtW6J0oTWs3Xy8XRa19htk.jpg 1792w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>While a complex model with more parameters can be more powerful, SLMs can still have an edge over LLMs. By being trained on smaller and more specialized datasets, SLMs \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fpulse\u002Fsmall-language-models-what-why-matter-vishnuvaradhan-v-0qypc\u002F\" target=\"_blank\">can be more efficient\u003C\u002Fa> for specific cases, even if this means having a narrower scope than LLMs.\u003C\u002Fp>\n\n\n\n\u003Cp>This can even lead to SLMs to outperform LLMs in certain cases. Microsoft exemplified this with their Phi-2 SLM, which \u003Ca href=\"http:\u002F\u002Fphi-2\">performed better\u003C\u002Fa> in coding and maths tasks compared to the Llama-2 LLM which is 25 times larger than Phi-2.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>SLMs’ potentials in healthcare\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>By focusing on curated, high-quality data and requiring less computational and financial resources, SLMs are particularly apt for healthcare uses. While GenAI which is based on SLMs has not been publicly released, we can contemplate some of the technology’s potential.\u003C\u002Fp>\n\n\n\n\u003Ch4 class=\"wp-block-heading\">1. Personalised patient journey\u003C\u002Fh4>\n\n\n\n\u003Cp>By training an SLM-based GenAI on relatively small but high-quality datasets, patients can receive a personalized healthcare experience. This can be achieved by developing a chatbot that focuses on a specific condition and can provide patients with educational materials and recommendations specific to their conditions. With such a tool, each patient could even have a personal, artificial doctor’s assistant that guides them during their patient journey.\u003C\u002Fp>\n\n\n\n\u003Ch4 class=\"wp-block-heading\">2. Affordable generative AI\u003C\u002Fh4>\n\n\n\n\u003Cp>By requiring fewer resources to train and run, SLMs are more affordable than their LLM counterparts. Such models could be deployed without the need for costly infrastructure such as specialised hardware and cloud services. Through such increased accessibility, more healthcare institutions could benefit from GenAI and further tune the technology to their individual needs, without compromising on efficiency. \u003C\u002Fp>\n\n\n\n\u003Ch4 class=\"wp-block-heading\">3. Improved AI transparency\u003C\u002Fh4>\n\n\n\n\u003Cp>Thanks to their simpler architecture, SLM outputs are more interpretable and thus more transparent. Transparency over such AI models is further enhanced by the ability to better control the training data to address biases and be more reflective of the population it is assisting. This can further help in building trust in such AI tools.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_363-768x432.png\" alt=\"\" class=\"wp-image-51097\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_363-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_363-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_363-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F05\u002Ftmf_article_363.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>While SLM tools have yet to be publicly deployed in healthcare settings, their advantages indicate that it is only a matter of time until this happens. Big tech companies are actively working on such models. Microsoft researchers have \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fnews.microsoft.com\u002Fthree-big-ai-trends-to-watch-in-2024\u002F\" target=\"_blank\">developed and released two SLMs\u003C\u002Fa>, namely Phi and Orca. French AI startup Mistral has \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.theinformation.com\u002Farticles\u002Fthe-rise-of-small-language-models-and-reinforcement-learning\" target=\"_blank\">released Mixtral-8x7B\u003C\u002Fa>, which can run on a single computer (with plenty of RAM). Google has \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Ftechcrunch.com\u002F2023\u002F12\u002F06\u002Fgoogles-gemini-isnt-the-generative-ai-model-we-expected\u002F\" target=\"_blank\">Gemini Nano\u003C\u002Fa>, which can run on smartphones.\u003C\u002Fp>\n\n\n\n\u003Cp>However, SLM tools will also bring about their respective concerns when they eventually roll out for healthcare purposes. They will have to adhere to similar \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhy-and-how-to-regulate-chatgpt-like-large-language-models-in-healthcare\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">regulations we propose for LLMs\u003C\u002Fa> in order to ensure their safe and ethical applications. As \u003Ca href=\"https:\u002F\u002Fnews.microsoft.com\u002Fthree-big-ai-trends-to-watch-in-2024\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Microsoft lists\u003C\u002Fa> SLMs as one of the big AI trends to watch in 2024, it might be worthwhile for the healthcare community to do the same.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>SLMs have relatively small number of parameters, and can, for example, run on an average mobile phone, without internet access.\u003C\u002Fp>\n",16,55149,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31],7079,[33,34,35],7915,7917,7741,[37],950,[],[40,41,42,43,44],1683,1833,2313,2693,4633,[46,14,47,48,49,50,51,52,53,54,55,56],"post-55115","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","tag-small-language-models","tag-slm","tag-large-language-models","project_category-medical-professionals",{"id":24,"alt_text":27,"caption":27,"description":27,"media_type":58,"media_details":59,"post":5,"source_url":99},"image",{"width":60,"height":61,"file":62,"filesize":63,"sizes":64,"image_meta":96},6667,3750,"2024\u002F03\u002Ftmf_article_404.png",1477675,{"medium":65,"large":72,"thumbnail":78,"medium_large":83,"1536x1536":84,"2048x2048":90},{"file":66,"width":67,"height":68,"mime-type":69,"filesize":70,"source_url":71},"tmf_article_404-370x208.png",370,208,"image\u002Fpng",34214,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404-370x208.png",{"file":73,"width":74,"height":75,"mime-type":69,"filesize":76,"source_url":77},"tmf_article_404-768x432.png",768,432,89420,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404-768x432.png",{"file":79,"width":80,"height":80,"mime-type":69,"filesize":81,"source_url":82},"tmf_article_404-150x150.png",150,16072,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404-150x150.png",{"file":73,"width":74,"height":75,"mime-type":69,"filesize":76,"source_url":77},{"file":85,"width":86,"height":87,"mime-type":69,"filesize":88,"source_url":89},"tmf_article_404-1536x864.png",1536,864,221872,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404-1536x864.png",{"file":91,"width":92,"height":93,"mime-type":69,"filesize":94,"source_url":95},"tmf_article_404-2048x1152.png",2048,1152,334238,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404-2048x1152.png",{"aperture":97,"credit":27,"camera":27,"caption":27,"created_timestamp":97,"copyright":27,"focal_length":97,"iso":97,"shutter_speed":97,"title":27,"orientation":97,"keywords":98},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F03\u002Ftmf_article_404.png",{"cta_type":101,"cta_color":27,"subtitle":27,"key_takeaways":102,"related_books":109,"related_posts_footer":113,"related_posts":20},"subscribe",[103,105,107],{"title":104},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">Small language models (SLMs) are gaining attention in the generative artificial intelligence field. SLMs are trained on relatively small amounts of data and have a relatively small number of parameters.\u003C\u002Fspan>\u003C\u002Fp>\n",{"title":106},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">SLM can be more practical than large language models as they are less resource intensive, without compromising on efficiency for specific use cases. \u003C\u002Fspan>\u003C\u002Fp>\n",{"title":108},"\u003Cp>\u003Cspan style=\"font-weight: 400;\">Potentials of SLM in healthcare include personalised patient journeys, making generative AI accessible to more institutions, and improving transparency over AI models.\u003C\u002Fspan>\u003C\u002Fp>\n",[110,111,112],52203,24761,47427,[114,115,116],55033,54593,54819,{"yoast_wpseo_title":17,"yoast_wpseo_metadesc":118,"yoast_wpseo_canonical":15},"SLMs have relatively small number of parameters, and can, for example, run on an average mobile phone, without internet access.",{"self":120,"collection":126,"about":129,"author":132,"replies":135,"version-history":138,"predecessor-version":142,"wp:featuredmedia":146,"wp:attachment":149,"wp:term":152,"curies":168},[121],{"href":122,"targetHints":123},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55115",{"allow":124},[125],"GET",[127],{"href":128},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[130],{"href":131},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[133],{"embeddable":26,"href":134},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[136],{"embeddable":26,"href":137},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=55115",[139],{"count":140,"href":141},15,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55115\u002Frevisions",[143],{"id":144,"href":145},55163,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F55115\u002Frevisions\u002F55163",[147],{"embeddable":26,"href":148},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F55149",[150],{"href":151},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=55115",[153,156,159,162,165],{"taxonomy":154,"embeddable":26,"href":155},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=55115",{"taxonomy":157,"embeddable":26,"href":158},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=55115",{"taxonomy":160,"embeddable":26,"href":161},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=55115",{"taxonomy":163,"embeddable":26,"href":164},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=55115",{"taxonomy":166,"embeddable":26,"href":167},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=55115",[169],{"name":170,"href":171,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[173],{"id":116,"date":174,"date_gmt":175,"guid":176,"modified":178,"modified_gmt":179,"slug":180,"status":13,"type":14,"link":181,"title":182,"content":184,"excerpt":186,"author":188,"featured_media":189,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":190,"categories":191,"tags":192,"project_category":193,"contact_email_category":195,"yst_prominent_words":196,"class_list":206,"better_featured_image":209,"acf":233,"yoast_meta":247,"_links":250},"2025-02-06T11:35:57","2025-02-06T10:35:57",{"rendered":177},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=54819&_wpnonce=4754b0943c&status=auto-draft&type=post","2025-02-19T09:01:33","2025-02-19T08:01:33","career-guide-in-digital-health-and-healthcare-ai","https:\u002F\u002Fmedicalfuturist.com\u002Fcareer-guide-in-digital-health-and-healthcare-ai",{"rendered":183},"Career Guide In Digital Health And Healthcare AI",{"rendered":185,"protected":20},"\n\u003Cp>It seems like every other day, someone reaches out to us – aiming their questions at Dr. Meskó, our lead researcher – seeking career advice. Now, let’s set the record straight: doling out career guidance isn’t exactly what we do. Yet, here we are, writing this article. Why? Even though we’re not career advisors, we’re right in the thick of the digital health and healthcare AI world. From this spot, we have a good overview of what you need to get into these booming fields. \u003C\u002Fp>\n\n\n\n\u003Cp>So, while we might not be career counselors, here are our two cents on which direction to take  – depending on the field from where you come.  Whether your background is tech-savvy, medically inclined, or somewhere in between, this article aims to share some straightforward advice to help you navigate your journey.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">1. For researchers\u003C\u002Fh2>\n\n\n\n\u003Cp>We’ve previously published our ‘\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftop-10-research-topics-to-pursue-in-digital-health\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Top 10 Research Topics To Pursue In Digital Health\u003C\u002Fa>,’ where we highlighted potential pathways for researchers. Although over a year has passed since its publication, we still stand by these topics and believe they hold great opportunities for those aspiring to make a mark in digital health and healthcare AI.\u003C\u002Fp>\n\n\n\n\u003Cp>Back then we defined four main pillars to determine if a topic was promising enough: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Find a niche\u003C\u002Fli>\n\n\n\n\u003Cli>Aim for uncharted territories\u003C\u002Fli>\n\n\n\n\u003Cli>Look for ease of entry\u003C\u002Fli>\n\n\n\n\u003Cli>Seek answers to important questions\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>We recommended research areas like \u003Cem>Diabetes management with wearable trackers including CGMs\u003C\u002Fem>, or \u003Cem>The impact of ECG smartwatches on unnecessary hospital admissions\u003C\u002Fem> and \u003Cem>Virtual reality (VR) therapies outside pain management and phobias \u003C\u002Fem>among others. But these are just a few ideas, so check your desired topics against our four pillars, and follow your own path!\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01-768x432.png\" alt=\"AI algorithm research topic digital health\" class=\"wp-image-47103\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01-2048x1152.png 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F08\u002Ftmf_article_331-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">2. With medical background\u003C\u002Fh2>\n\n\n\n\u003Cp>Entering the field of digital health and healthcare AI with a medical background presents a unique advantage. Every company in this space needs medical supervision to ensure their developments \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fis-it-revolutionary-a-6-question-checklist-to-assess-any-digital-health-announcement\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">meet real clinical and medical needs\u003C\u002Fa>. But, to efficiently navigate this realm, you must understand the technology you’re working with.\u003C\u002Fp>\n\n\n\n\u003Cp>It’s not about becoming a developer or data science master but grasping the technological challenges developers face when creating healthcare solutions. Linking clinical requirements and technological capabilities will significantly enhance the effectiveness of these solutions.\u003C\u002Fp>\n\n\n\n\u003Cp>To this end, pursuing courses that provide insight into the intersection of medicine and technology is highly beneficial. Similarly, engaging with scientific literature on this topic can deepen your understanding, so look for papers like Dr. Meskó’s “\u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41746-020-00333-z\" target=\"_blank\" rel=\"noreferrer noopener\">A Short guide for medical professionals in the era of artificial intelligence\u003C\u002Fa>,” which serves as a great starting point for medical professionals keen on navigating the healthcare AI landscape.\u003C\u002Fp>\n\n\n\n\u003Cp>This approach leads you to the digital health field while also ensuring that technological innovations focus on genuine healthcare needs, resulting in patient-centered solutions.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">3. With tech background\u003C\u002Fh2>\n\n\n\n\u003Cp>If your expertise lies in the tech realm, the key to making a meaningful impact in digital health and healthcare AI is to develop a thorough understanding of real medical, clinical, and \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fare-you-too-old-to-use-digital-health\" target=\"_blank\" rel=\"noreferrer noopener\">patient needs\u003C\u002Fa>. Developing technology for its own sake, without a clear application in the clinical world, is unlikely to stand the test of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ften-ways-technology-changing-healthcare\" target=\"_blank\" rel=\"noreferrer noopener\">real-world healthcare challenges\u003C\u002Fa>. Tech professionals need to grasp the medical and, most importantly, the patient perspective, should we talk about physical products, research or clinical design. We discussed these with real-life examples in detail \u003Ca href=\"https:\u002F\u002Fwww.jmir.org\u002F2022\u002F8\u002Fe39178\" target=\"_blank\" rel=\"noreferrer noopener\">in this paper\u003C\u002Fa>, the common denominator is that we need to understand what patients want to improve. \u003C\u002Fp>\n\n\n\n\u003Cp>The current AI revolution offers great healthcare opportunities for data scientists, or AI developers building neural networks and\u002For large language models (just to name a few examples). They don’t need to graduate from a medical university to connect tech advancements to practical problems to create tangible results.\u003C\u002Fp>\n\n\n\n\u003Cp>Focusing on patient design and incorporating feedback from medical professionals can bridge the gap between technological potential and healthcare reality, creating solutions that are both innovative and genuinely beneficial to patients.\u003C\u002Fp>\n\n\n\n\u003Cp>Engaging in patient-centered design is an excellent direction for tech professionals entering the healthcare space.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_technological-advances-in-the-future-of-medicine2-768x432.png\" alt=\"\" class=\"wp-image-53955\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_technological-advances-in-the-future-of-medicine2-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_technological-advances-in-the-future-of-medicine2-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_technological-advances-in-the-future-of-medicine2-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_technological-advances-in-the-future-of-medicine2.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">4. For those transitioning from traditional med-tech to digital health\u003C\u002Fh2>\n\n\n\n\u003Cp>Individuals with a background in medical technology, and especially those who exclusively develop solutions for medical professionals, face a unique transition when moving into the digital health sector. This shift requires an in-depth understanding of the \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-health-technologies\" target=\"_blank\" rel=\"noreferrer noopener\">fundamentals of digital health\u003C\u002Fa> and the ongoing paradigm shift and cultural revolution transforming the healthcare landscape.\u003C\u002Fp>\n\n\n\n\u003Cp>Such a move represents a significant change, not just in technology but in mindset and application. Developing for digital health diverges from traditional medical settings in several crucial factors. \u003C\u002Fp>\n\n\n\n\u003Cp>As digital health typically targets a broader user base, including patients, caregivers, and healthcare consumers, a user-friendly design and an intuitive interface accessible to non-professionals is a must. The \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fbeyond-the-hype-the-top-5-digital-health-devices-making-a-real-difference-in-my-life\" target=\"_blank\" rel=\"noreferrer noopener\">development of digital health solutions\u003C\u002Fa> frequently involves a diverse mix of expertise, potentially including elements from data science, user experience design, and behavioral science, beyond traditional engineering and medical expertise.\u003C\u002Fp>\n\n\n\n\u003Cp>Another factor to keep in mind is the drastically different approach to data. Digital health initiatives, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-health-manifesto\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">by definition\u003C\u002Fa>, aim to make health data more accessible and understandable to patients, empowering them to take an active role in their health management. This is a shift from med-tech’s guarded approach to medical data. With this comes the last unique factor: field-specific challenges of data privacy and security, which are the basics of creating safe digital health spaces. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">5. For biomedical engineers\u003C\u002Fh2>\n\n\n\n\u003Cp>Biomedical engineering stands at the crossroads of engineering and healthcare, representing a field where specialists have a firm understanding of both technology and the foundational elements of digital health. \u003C\u002Fp>\n\n\n\n\u003Cp>For biomedical engineers, the likely focus for further development should be on honing their communication skills with doctors and patients alike. While they possess the technical expertise and have a grasp on the medical and patient perspectives, the ability to effectively communicate and translate complex technical concepts into actionable, understandable information for medical professionals and laypersons is paramount.\u003C\u002Fp>\n\n\n\n\u003Cp>Their unique position allows them to serve as a central “\u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-would-make-every-doctor-use-digital-health\" target=\"_blank\" rel=\"noreferrer noopener\">communication hub\u003C\u002Fa>” between patients, healthcare professionals, and tech teams. Ideally, this ensures that innovations align with the real-world needs of healthcare providers and patients.\u003C\u002Fp>\n\n\n\n\u003Cp>We’re living in a fascinating era where fields that were once miles apart are now converging to develop health-related products and services. This convergence creates previously unseen collaborations and overlaps. Due to this, a “hodgepodge” of knowledge from different domains can become highly sought after, favoring generalists – people proficient in multiple areas. \u003C\u002Fp>\n\n\n\n\u003Cp>Having said all that, the guiding principle for navigating one’s career should not be to follow the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmedical-specialties-with-the-biggest-potential-in-the-future\" target=\"_blank\">top lists\u003C\u002Fa> but be driven by curiosity and belief in\u002Fpassion for the path chosen.\u003C\u002Fp>\n",{"rendered":187,"protected":20},"\u003Cp>Whether your background is tech-savvy, medically inclined, or somewhere in between, this article aims to share some straightforward advice to help you navigate your journey.\u003C\u002Fp>\n",6,54827,{"_acf_changed":20,"footnotes":27},[31],[],[194,37],949,[],[197,40,198,199,200,201,41,202,203,204,205],1681,1693,1719,1723,1739,3615,1571,1617,1631,[207,14,47,48,49,50,51,52,208,56],"post-54819","project_category-educators",{"id":189,"alt_text":210,"caption":27,"description":27,"media_type":58,"media_details":211,"post":116,"source_url":232},"career doctor TMF",{"width":212,"height":213,"file":214,"filesize":215,"sizes":216,"image_meta":230},1280,720,"2024\u002F02\u002Ftmf_article_401ai.png",1633636,{"medium":217,"large":221,"thumbnail":225,"medium_large":229},{"file":218,"width":67,"height":68,"mime-type":69,"filesize":219,"source_url":220},"tmf_article_401ai-370x208.png",98886,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_401ai-370x208.png",{"file":222,"width":74,"height":75,"mime-type":69,"filesize":223,"source_url":224},"tmf_article_401ai-768x432.png",454186,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_401ai-768x432.png",{"file":226,"width":80,"height":80,"mime-type":69,"filesize":227,"source_url":228},"tmf_article_401ai-150x150.png",28717,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_401ai-150x150.png",{"file":222,"width":74,"height":75,"mime-type":69,"filesize":223,"source_url":224},{"aperture":97,"credit":27,"camera":27,"caption":27,"created_timestamp":97,"copyright":27,"focal_length":97,"iso":97,"shutter_speed":97,"title":27,"orientation":97,"keywords":231},[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F02\u002Ftmf_article_401ai.png",{"cta_type":101,"cta_color":27,"related_books":234,"related_posts_footer":237,"related_posts":20,"subtitle":27,"key_takeaways":240},[235,111,236],30419,31417,[238,115,239],54743,54435,[241,243,245],{"title":242},"\u003Cp>Fields that were once miles apart are now converging to develop health-related products and services, and this convergence creates previously unseen collaborations and overlaps.\u003C\u002Fp>\n",{"title":244},"\u003Cp>Thus a “hodgepodge” of knowledge from different domains can become highly sought after, favoring generalists – people proficient in multiple areas\u003C\u002Fp>\n",{"title":246},"\u003Cp>As how to enter the digital health and healthcare AI fields with various backgrounds is a question we get daily, here are our two cents based on your initial background.\u003C\u002Fp>\n",{"yoast_wpseo_title":248,"yoast_wpseo_metadesc":249,"yoast_wpseo_canonical":181},"Career Guide In Digital Health And Healthcare AI - The Medical Futurist","Whether your background is tech-savvy, medically inclined, or somewhere in between, here is some straightforward advice to help you navigate your journey.",{"self":251,"collection":256,"about":258,"author":260,"replies":263,"version-history":266,"predecessor-version":270,"wp:featuredmedia":274,"wp:attachment":277,"wp:term":280,"curies":291},[252],{"href":253,"targetHints":254},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54819",{"allow":255},[125],[257],{"href":128},[259],{"href":131},[261],{"embeddable":26,"href":262},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[264],{"embeddable":26,"href":265},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=54819",[267],{"count":268,"href":269},12,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54819\u002Frevisions",[271],{"id":272,"href":273},58521,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F54819\u002Frevisions\u002F58521",[275],{"embeddable":26,"href":276},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F54827",[278],{"href":279},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=54819",[281,283,285,287,289],{"taxonomy":154,"embeddable":26,"href":282},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=54819",{"taxonomy":157,"embeddable":26,"href":284},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=54819",{"taxonomy":160,"embeddable":26,"href":286},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=54819",{"taxonomy":163,"embeddable":26,"href":288},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=54819",{"taxonomy":166,"embeddable":26,"href":290},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=54819",[292],{"name":170,"href":171,"templated":26},[294],{"id":112,"date":295,"date_gmt":296,"guid":297,"modified":299,"modified_gmt":300,"slug":301,"status":13,"type":302,"link":303,"title":304,"content":306,"excerpt":308,"author":188,"featured_media":310,"comment_status":25,"ping_status":25,"template":27,"yst_prominent_words":311,"class_list":313,"better_featured_image":316,"acf":336,"yoast_meta":342,"_links":345},"2022-09-29T09:59:00","2022-09-29T07:59:00",{"rendered":298},"https:\u002F\u002Fapi.medicalfuturist.com\u002F?post_type=book&p=47427","2023-03-12T18:17:06","2023-03-12T17:17:06","a-guide-to-the-future-of-hospitals","book","https:\u002F\u002Fapi.medicalfuturist.com\u002Fbooks\u002Fa-guide-to-the-future-of-hospitals\u002F",{"rendered":305},"A Guide To The Future Of Hospitals – The Medical Futurist",{"rendered":307,"protected":20},"\n\u003Cp>Learn how hospitals of the future will be designed, and what technologies will be used in hospitals to change the healthcare experience for all.\u003C\u002Fp>\n",{"rendered":309,"protected":20},"\u003Cp>Learn how hospitals of the future will be designed, and what technologies will be used in hospitals to change the healthcare experience for all.\u003C\u002Fp>\n",49951,[312],2605,[314,302,315,48,50,51],"post-47427","type-book",{"id":310,"alt_text":27,"caption":27,"description":27,"media_type":58,"media_details":317,"post":112,"source_url":335},{"width":318,"height":319,"file":320,"filesize":321,"sizes":322,"image_meta":334},320,414,"2022\u002F09\u002Fguide-to-the-future-of-hospitals.png",32249,{"medium":323,"thumbnail":329},{"file":324,"width":325,"height":326,"mime-type":69,"filesize":327,"source_url":328},"guide-to-the-future-of-hospitals-320x208.png","320","208","51648","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fguide-to-the-future-of-hospitals-320x208.png",{"file":330,"width":331,"height":331,"mime-type":69,"filesize":332,"source_url":333},"guide-to-the-future-of-hospitals-150x150.png","150","24145","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fguide-to-the-future-of-hospitals-150x150.png",{"aperture":97,"credit":27,"camera":27,"caption":27,"created_timestamp":97,"copyright":27,"focal_length":97,"iso":97,"shutter_speed":97,"title":27,"orientation":97},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002Fguide-to-the-future-of-hospitals.png",{"buy_button_text":337,"leanpub_url":338,"preview":339},"Get it on Leanpub","https:\u002F\u002Fleanpub.com\u002Ffuture-of-hospitals",[340],{"image":341},"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F09\u002F0926_Future_of_Hospitals_Cover.png",{"yoast_wpseo_title":343,"yoast_wpseo_metadesc":344,"yoast_wpseo_canonical":303},"A Guide To The Future Of Hospitals - The Medical Futurist - The Medical Futurist","Learn how hospitals of the future will be designed, and what technologies will be used in hospitals to change the healthcare experience for all.",{"self":346,"collection":351,"about":354,"author":357,"replies":359,"wp:featuredmedia":362,"wp:attachment":365,"wp:term":368,"curies":371},[347],{"href":348,"targetHints":349},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook\u002F47427",{"allow":350},[125],[352],{"href":353},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fbook",[355],{"href":356},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fbook",[358],{"embeddable":26,"href":262},[360],{"embeddable":26,"href":361},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=47427",[363],{"embeddable":26,"href":364},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F49951",[366],{"href":367},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=47427",[369],{"taxonomy":166,"embeddable":26,"href":370},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=47427",[372],{"name":170,"href":171,"templated":26},1785589597886]