[{"data":1,"prerenderedAt":165},["ShallowReactive",2],{"slug-the-healthcare-ai-strategy-of-china":3},{"post":4,"relatedPosts":163,"relatedBooks":164},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":34,"project_category":35,"contact_email_category":36,"yst_prominent_words":37,"class_list":46,"better_featured_image":56,"acf":100,"yoast_meta":108,"_links":110},60483,"2026-03-20T10:40:03","2026-03-20T09:40:03",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=60483&_wpnonce=0638969cf5&status=auto-draft&type=post","2026-03-20T10:40:06","2026-03-20T09:40:06","the-healthcare-ai-strategy-of-china","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fthe-healthcare-ai-strategy-of-china",{"rendered":17},"The Healthcare AI Strategy Of China",{"rendered":19,"protected":20},"\n\u003Cp>Recently, an interesting development has occurred in the field of healthcare artificial intelligence (AI). The world’s largest health-focused AI app \u003Ca href=\"https:\u002F\u002Fpandaily.com\u002Fant-group-s-spring-festival-report-ai-payments-and-health-app-users-both-surpass-100-million\">emerged from China\u003C\u002Fa>, with over 100 million users. Ant Group’s AI-powered health app A-Fu has been helping clinicians in remote areas interpret medical reports and build health records for chronic disease patients. Other users are adopting it to query everyday health concerns, such as understanding medication labels and assessing symptoms. This development piqued our interest. \u003C\u002Fp>\n\n\n\n\u003Cp>There is no shortage of potential for AI in healthcare. From assisting doctors with \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fhow-much-time-can-ai-scribes-save\">tedious administrative tasks\u003C\u002Fa> and accompanying patients in \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fai-in-the-patient-journey-infographic\">their medical journey\u003C\u002Fa> to aiding pharma companies \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Ftop-digital-health-and-healthcare-ai-trends-to-watch-in-2026\">in drug discovery\u003C\u002Fa> and supporting \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-medical-futurists-100-digital-health-and-ai-companies-of-2026\">medical imaging diagnostics\u003C\u002Fa>, there doesn’t seem to be a sector that the technology cannot disrupt.  \u003C\u002Fp>\n\n\n\n\u003Cp>Even if these potentials have been put into practice in pilot or specific scenarios, their broad-scale adoption hasn’t been realised. China might be on the way to supercharge this uptake at a national level, implementing AI technology across its healthcare ecosystem for its \u003Ca href=\"https:\u002F\u002Fwww.worldometers.info\u002Fworld-population\u002Fchina-population\u002F\">1.4 billion inhabitants\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cp>The country’s authorities have recently called for the broader adoption of healthcare AI across the country, with several regions working towards such implementation and investments funnelled in the same direction. We unpack the implications in this article.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>China’s healthcare AI vision \u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>In late 2025, China’s National Health Commission and four other authorities \u003Ca href=\"https:\u002F\u002Fenglish.www.gov.cn\u002Fnews\u002F202511\u002F04\u002Fcontent_WS690a0437c6d00ca5f9a0751a.html\">issued a call\u003C\u002Fa> for the broader application of AI in the country’s health sector. The vision is a bold one: AI-assisted diagnosis and treatment will be the standard across primary-level institutions for 900 million citizens by 2030. \u003C\u002Fp>\n\n\n\n\u003Cp>For institutions at or above the secondary level in the country’s three-tiered hospital system, AI will be deployed to support medical imaging diagnosis and clinical decision-making. Patient services, such as scheduling and triage, are also expected to integrate AI support.\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\u002F12\u002Ftmf_article_394-768x432.png\" alt=\"\" class=\"wp-image-54109\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F12\u002Ftmf_article_394.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>This call isn’t merely an effort to brand a healthcare institution as being “AI-branded” but aims to bring positive change. For instance, this strategy \u003Ca href=\"https:\u002F\u002Fopengovasia.com\u002Fchina-unveils-national-ai-healthcare-strategy-a-medical-revolution-in-the-making\u002F\">aims to reduce\u003C\u002Fa> misdiagnosis in primary care from around 40-50% to about 15-20%, reach 95% diagnostic accuracy in medical imaging, and close the gap between urban and rural healthcare access.\u003C\u002Fp>\n\n\n\n\u003Cp>The Chinese authorities propose \u003Ca href=\"https:\u002F\u002Fopengovasia.com\u002Fchina-unveils-national-ai-healthcare-strategy-a-medical-revolution-in-the-making\u002F\">a phased implementation\u003C\u002Fa> to enact this plan. In 2026, pilots for AI diagnostic tools are set for 50 hospitals and 500 township clinics. Each level of care is expected to have a unified national health database in 2027, leading to the nationwide accessibility of AI-assisted diagnoses in 2030. Within this 5-year timeline, \u003Ca href=\"https:\u002F\u002Fopengovasia.com\u002Fchina-unveils-national-ai-healthcare-strategy-a-medical-revolution-in-the-making\u002F\">an investment rollout of between $2-3 billion\u003C\u002Fa> is planned.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Practical efforts towards China’s health AI strategy\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>China’s outlook on AI integration in healthcare goes beyond individual tools and considers the technology as a foundational element in the infrastructure of its digital health efforts. The country has undergone \u003Ca href=\"https:\u002F\u002Fwww.medbridgenz.com\u002Fpost\u002Finside-china-s-world-class-hospitals-what-makes-them-so-advanced\">comprehensive reforms\u003C\u002Fa>, with strong government policy and support, to support the digitalisation of its health sector. This has encouraged the adoption of digital health and health IT tools \u003Ca href=\"https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC12520162\u002F\">with stronger levels\u003C\u002Fa> of data interoperability and system compatibility than in other jurisdictions. In contrast, other countries like the UK and the US that suffer from insufficient data integration and misaligned workflows \u003Ca href=\"https:\u002F\u002Fwww.weforum.org\u002Fstories\u002F2025\u002F03\u002Fai-healthcare-strategy-speed\u002F\">can exacerbate challenges\u003C\u002Fa> such as inefficiencies and misaligned priorities.\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\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif\" alt=\"voice to text technologies\" class=\"wp-image-24827\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-768x432.gif 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-370x208.gif 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-1536x864.gif 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-2048x1152.gif 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2019\u002F09\u002F106_Voice-to-text-technologies-in-medicine-512x288.gif 512w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Chinese provinces are already heeding to the call for health AI integration. Among the most recent pilots \u003Ca href=\"https:\u002F\u002Fwww.healthcareitnews.com\u002Fnews\u002Fasia\u002Fai-expands-through-chinas-healthcare-reform-pilots%C2%A0\">comes from Jiangsu Province\u003C\u002Fa>. In one of its cities, Suzhou, a personal AI health assistant has been deployed to personalise the health profile of citizens by analysing their annual physical examination reports and medical records. Also piloted in the city are AI GPs that have assisted over 5 million people in pre-consultations, diagnosis, and case and prescription reviews.\u003C\u002Fp>\n\n\n\n\u003Cp>Several other regions, including Beijing, Shanghai, Zhejiang, Henan and Hefei, \u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\">have shared plans\u003C\u002Fa> for their own health AI pilot projects. Such efforts are in line with the Chinese authorities’ call for broader implementation of the technology, and 2026 is looking to be a year rich in health AI pilots in the Far East.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The AI push from tech companies\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>This national incentive has also driven Chinese tech companies to accelerate the development of their AI models to get a lead in the health sector. Some have spent \u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\">hundreds of millions\u003C\u002Fa> of Chinese yuan on advertisements alone, while others have jumped onto the AI boom bandwagon to offer healthcare-facing models.\u003C\u002Fp>\n\n\n\n\u003Cp>E-commerce giant Alibaba’s model dedicated for healthcare uses showed promise in 2025 when \u003Ca href=\"https:\u002F\u002Fwww.scmp.com\u002Ftech\u002Ftech-trends\u002Farticle\u002F3312153\u002Falibabas-healthcare-ai-model-scores-high-senior-level-doctors-medical-exams\">its benchmark scores\u003C\u002Fa> indicated capabilities equivalent to experienced doctors. The model has been integrated into its consumer-facing AI assistant app, Quark. Another major Chinese tech company, Tencent, invested in healthcare AI projects. Its has \u003Ca href=\"https:\u002F\u002Fwww.tencent.com\u002Fen-us\u002Farticles\u002F2202132.html\">developed several AI models\u003C\u002Fa> for different use cases in this sector. For example, its Hunyuan model provides smart health checkup service, while its Qiyuan model helps train doctors to better respond in ICU situations.\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\u002F2025\u002F02\u002Ftmf_article_436-768x432.png\" alt=\"\" class=\"wp-image-58513\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_436-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_436-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_436-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2025\u002F02\u002Ftmf_article_436-2048x1152.png 2048w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Models from Chinese tech companies iFlytek, Quark Health and Baichuan Intelligence have proven their medical aptitude \u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\">by passing\u003C\u002Fa> the country’s National Medical Licensing Examination.\u003C\u002Fp>\n\n\n\n\u003Cp>Large language models Doubao, Baichuan, Xiaohe, ChatGPT o1 and Gemini \u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\">have been pitted\u003C\u002Fa> against actual doctors, with promising results. During competitions, human doctors were found to perform better in the definitive diagnosis and treatment planning phase, while AI models could even outperform them in some cases.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>How realistic is China’s health AI strategy?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The big, bold call from Chinese authorities has no equivalent in terms of its sheer reach, so it’s fair to have a layer of scepticism when looking at this ambitious strategy from the outside. \u003C\u002Fp>\n\n\n\n\u003Cp>With basic services being available for free, concerns arise regarding the return-on-investment for AI-assisted consultations. The developers behind such models require extensive resources, from high-quality training data to maintaining servers, to provide these automated tools. \u003C\u002Fp>\n\n\n\n\u003Cp>“When we discuss [business models] internally, there is a lot of controversy,”\u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\"> revealed Chen Liang\u003C\u002Fa>, senior vice president and chief marketing officer of Ant Group, revealed during a media briefing in December 2025. “We argued for a long time and, frankly speaking, there is no answer.”\u003C\u002Fp>\n\n\n\n\u003Cp>This is a surprising admission, especially considering that Ant, Alibaba’s fintech affiliate, has \u003Ca href=\"https:\u002F\u002Frestofworld.org\u002F2026\u002Fai-health-care-is-taking-off-in-china-led-by-jack-mas-ant-group\u002F\">one of the most used\u003C\u002Fa> health chatbots in the country, Ant Afu. But Liang believes in the long-term game. According to him, Ant Afu will help the ageing population, thereby \u003Ca href=\"https:\u002F\u002Fwww.thinkchina.sg\u002Ftechnology\u002Fchinas-tech-giants-burn-cash-try-dominate-ai-healthcare\">creating value for society\u003C\u002Fa> that will lead to a business model.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"430\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fhealth-ai-ant-group-768x430.jpg\" alt=\"\" class=\"wp-image-60485\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fhealth-ai-ant-group-768x430.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fhealth-ai-ant-group-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fhealth-ai-ant-group.jpg 1237w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption class=\"wp-element-caption\">Source: https:\u002F\u002Frestofworld.org\u002F\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>There are \u003Ca href=\"https:\u002F\u002Fpmc.ncbi.nlm.nih.gov\u002Farticles\u002FPMC12638562\u002F\">more hurdles\u003C\u002Fa> than economic viability to overcome. Proprietary AI algorithms have to be explainable for healthcare usage. Frameworks for medical liability are unclear in cases of AI-assisted decision-making that conflict with clinicans’ judgement. Despite measures for interoperability, there are still fragmentation in the system to be addressed.\u003C\u002Fp>\n\n\n\n\u003Cp>China’s phased implementation strategy might work towards a step-wise approach to address such hurdles while assessing the success of its AI implementation pilots. If the country achieves its goals within 5 years, the result might represent the biggest digital health transformation in the current era and a major move forward for healthcare AI. There will certainly be lessons learnt along the way, but these can inform the strategies of other jurisdictions as they pave their own AI-driven healthcare paths.\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>Recently, an interesting development has occurred in the field of healthcare artificial intelligence (AI). The world’s largest health-focused AI app emerged from China, with over […]\u003C\u002Fp>\n",16,60487,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32,33],521,499,800,[],[],[],[38,39,40,41,42,43,44,45],1571,1617,1683,1723,1783,1833,2343,2583,[47,14,48,49,50,51,52,53,54,55],"post-60483","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-future-medicine","category-healthcare-design","category-healthcare-policy",{"id":24,"alt_text":27,"caption":27,"description":27,"media_type":57,"media_details":58,"post":5,"source_url":99},"image",{"width":59,"height":60,"file":61,"filesize":62,"sizes":63,"image_meta":95,"original_image":98},2560,1440,"2026\u002F03\u002Fchina-healthcare-AI-strategy-scaled.jpg",190913,{"medium":64,"large":71,"thumbnail":77,"medium_large":82,"1536x1536":83,"2048x2048":89},{"file":65,"width":66,"height":67,"mime-type":68,"filesize":69,"source_url":70},"china-healthcare-AI-strategy-370x208.jpg",370,208,"image\u002Fjpeg",36885,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-370x208.jpg",{"file":72,"width":73,"height":74,"mime-type":68,"filesize":75,"source_url":76},"china-healthcare-AI-strategy-768x432.jpg",768,432,55549,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-768x432.jpg",{"file":78,"width":79,"height":79,"mime-type":68,"filesize":80,"source_url":81},"china-healthcare-AI-strategy-150x150.jpg",150,29740,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-150x150.jpg",{"file":72,"width":73,"height":74,"mime-type":68,"filesize":75,"source_url":76},{"file":84,"width":85,"height":86,"mime-type":68,"filesize":87,"source_url":88},"china-healthcare-AI-strategy-1536x864.jpg",1536,864,105865,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-1536x864.jpg",{"file":90,"width":91,"height":92,"mime-type":68,"filesize":93,"source_url":94},"china-healthcare-AI-strategy-2048x1152.jpg",2048,1152,147396,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-2048x1152.jpg",{"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",[],"china-healthcare-AI-strategy.jpg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F03\u002Fchina-healthcare-AI-strategy-scaled.jpg",{"subtitle":27,"key_takeaways":101,"cta_type":27,"cta_color":27,"related_books":20,"related_posts_footer":20,"related_posts":20},[102,104,106],{"title":103},"\u003Cp>China’s National Health Commission and four other authorities have issued a call for the broader application of AI in the country’s health sector.\u003C\u002Fp>\n",{"title":105},"\u003Cp>Chinese provinces and tech companies alike are already heeding to the call for health AI integration, with multiple pilots underway and solutions on the market.\u003C\u002Fp>\n",{"title":107},"\u003Cp>There are several hurdles to overcome for this healthcare AI strategy to become successful, and there will be lessons learned that can inform future strategies in other jurisdictions.\u003C\u002Fp>\n",{"yoast_wpseo_title":109,"yoast_wpseo_metadesc":27,"yoast_wpseo_canonical":15},"The Healthcare AI Strategy Of China - The Medical Futurist",{"self":111,"collection":117,"about":120,"author":123,"replies":126,"version-history":129,"predecessor-version":133,"wp:featuredmedia":137,"wp:attachment":140,"wp:term":143,"curies":159},[112],{"href":113,"targetHints":114},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60483",{"allow":115},[116],"GET",[118],{"href":119},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[121],{"href":122},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[124],{"embeddable":26,"href":125},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[127],{"embeddable":26,"href":128},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=60483",[130],{"count":131,"href":132},1,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60483\u002Frevisions",[134],{"id":135,"href":136},60489,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F60483\u002Frevisions\u002F60489",[138],{"embeddable":26,"href":139},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F60487",[141],{"href":142},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=60483",[144,147,150,153,156],{"taxonomy":145,"embeddable":26,"href":146},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=60483",{"taxonomy":148,"embeddable":26,"href":149},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=60483",{"taxonomy":151,"embeddable":26,"href":152},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=60483",{"taxonomy":154,"embeddable":26,"href":155},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=60483",{"taxonomy":157,"embeddable":26,"href":158},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=60483",[160],{"name":161,"href":162,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[],[],1786260356331]