"我头很疼""您最近有没有压力大？睡不好？我教您几个放松的动作"……问答中，基于人工智能医疗大 模型开发的"数字医生"为居民提供了个性化健康管理建议。 辅助诊疗、处方审核等智能应用，让基层医生有了帮手；上传舌诊照片，中医智能诊断设备可辨识患者 健康状态……近年来，人工智能广泛应用于医学影像诊断、临床决策支持、慢病管理等多个医疗领域场 景。"促进人工智能在医疗卫生领域的规范应用，不断丰富应用场景，提升服务能力，保障服务安全， 优化资源配置，更好满足人民群众日益增长的健康服务需求。"国家卫生健康委有关负责人介绍。 到2030年基本实现基层诊疗智能辅助应用全覆盖 促进规范人工智能深度融入健康服务(政策速递) 本报记者 杨彦帆 《人民日报》(2025年11月30日 第 02 版) 北京市海淀区花园路社区卫生服务中心，门诊大厅的"数字医生"交互屏吸引不少居民驻足。 突出基层。提出加强紧密型县域医共体智能应用，建立基层医生智能辅助诊疗应用，加强居民慢性病规 范管理服务，强化健康管理、养老和托育服务。比如建立智能慢性病管理和个人健康画像应用，推动居 民电子健康档案规范向个人开放；推广老年人、孕产妇、儿童等重点人群的健康管理 ...

Core Viewpoint - The integration of artificial intelligence (AI) in healthcare is being promoted to enhance service capabilities, optimize resource allocation, and meet the growing health service demands of the population [1][2][3] Group 1: AI Applications in Healthcare - AI technologies are being applied in various medical fields, including medical imaging diagnosis, clinical decision support, and chronic disease management [1] - The implementation of AI in healthcare aims to provide personalized health management suggestions and assist primary care physicians with diagnostic and treatment processes [1][2] Group 2: Implementation Guidelines - Five departments have released guidelines to promote and regulate the application of AI in healthcare, with a timeline set for 2030 to achieve comprehensive coverage of intelligent assistance in primary care [1][2] - Specific measures include promoting intelligent diagnostic services, expanding clinical decision support applications, and enhancing chronic disease management services [2] Group 3: Focus Areas - The guidelines emphasize the importance of grassroots applications, clinical diagnosis, patient services, and public health [2] - There is a focus on developing intelligent health management services, including health consultations and personalized health profiles for chronic disease management [2] Group 4: Regulatory and Safety Measures - The approach to AI in healthcare emphasizes empowerment rather than replacement, with a commitment to optimizing industry management and enhancing data security and privacy protection [3] - Plans include establishing clinical specialty data sets and AI corpus, as well as creating a public support service platform for vertical AI models in the healthcare sector [3]

Core Viewpoint - The integration of artificial intelligence (AI) in healthcare is being promoted to enhance service capabilities, optimize resource allocation, and meet the growing health service demands of the population by 2030 [1][2][3] Group 1: AI Applications in Healthcare - AI is being widely applied in various medical fields, including medical imaging diagnosis, clinical decision support, and chronic disease management [1] - The implementation plan emphasizes the need for AI applications to be driven by real business scenarios and to address actual needs, focusing on grassroots applications, clinical diagnosis, patient services, and public health [2] Group 2: Development Goals and Timeline - By 2030, the goal is to achieve full coverage of intelligent assistance applications in grassroots diagnosis and treatment, with secondary hospitals widely adopting AI technologies for medical imaging and clinical decision support [1][2] - A comprehensive standard and regulatory framework for "AI + healthcare" applications is expected to be established, along with the creation of leading technology innovation and talent training bases [1] Group 3: Focus Areas for Implementation - The plan highlights the importance of strengthening intelligent applications in tightly-knit county medical communities and enhancing chronic disease management services [2] - It encourages the development of new service models such as intelligent health check-ups, health consultations, and health management, while supporting collaboration between medical equipment manufacturers and healthcare institutions [2] Group 4: Regulatory and Safety Measures - The initiative aims to ensure that AI empowers rather than replaces healthcare professionals, optimizing industry management and regulatory systems while enhancing data security and personal privacy protection [3] - The establishment of clinical specialty data sets and AI corpus, along with a public support service platform for vertical AI models, is being explored to facilitate the effective implementation of AI in healthcare [3]

Group 1 - The core viewpoint of the news is the launch of action plans in Zhejiang Province aimed at accelerating the development of first stores and promoting artificial intelligence in healthcare, which is expected to benefit the consumption and technology industries [1] Group 2 - The action plan for first store development aims to add over 2,000 urban brand first stores in the province by 2027, including 200 high-energy first stores in the East China region [1] - The plan emphasizes attracting high-quality product first stores, targeting the addition of over 1,000 product brand first stores by 2027 [1] - It also focuses on nurturing innovative service first stores, with a goal of adding over 1,000 service brand first stores by 2027 [1] - The initiative includes the creation of over 20 first store enhancement zones to support county-level development and drive consumption upgrades by 2027 [1] - The plan outlines measures to optimize the business environment, including streamlining approval processes and promoting online and offline service collaboration [1] Group 3 - The action plan for "Artificial Intelligence + Healthcare" aims to establish a national-level application base for AI in the healthcare industry by 2027, fostering clusters and developing a corpus and models [1] - It emphasizes the need to break through core technologies and build key scenarios while nurturing enterprises and talent to create an innovation chain [1] - The plan promotes AI to enhance public health, iterating on digital health personnel and popularizing digital doctors [1] - It also focuses on the development of future hospitals, enhancing diagnostic and treatment capabilities across seven innovative fields [1] - The initiative supports the formation of innovative coalitions to encourage industry integration and collaborative networks around technology research and application [1]

Core Viewpoint - Beijing aims to accelerate the development of the "Artificial Intelligence + Healthcare" sector, establishing itself as an international innovation hub by 2027 through a comprehensive action plan [3][4]. Group 1: Development Goals - Leverage Beijing's advantages in AI technology, medical resources, and health data to create a dual innovation and application ecosystem in the "Artificial Intelligence + Healthcare" industry by 2027 [4]. - Achieve the transformation of over 30 core technologies and innovative products, with at least 20 innovative drugs and medical devices entering clinical trials [4]. - Promote the application of AI in various healthcare scenarios, including medical services and public health, with a focus on at least 10 specific applications [4]. Group 2: Key Tasks - **Basic Research Breakthroughs**: Explore new paradigms in life sciences driven by AI, focusing on foundational theories and algorithms [6]. - **Data Resource Construction**: Accelerate the establishment of a comprehensive health information platform to integrate various health data sources [8]. - **AI Empowerment in Healthcare**: Support the development of AI applications in drug discovery, personalized medicine, and smart healthcare services [10][11]. Group 3: Innovation Ecosystem - Establish innovation incubators and accelerate platforms to enhance the efficiency of transforming innovative results into practical applications [17]. - Foster collaboration among medical, industrial, academic, and research entities to create competitive industry clusters [5][19]. - Develop a technical standard system to ensure the reliability and compatibility of AI healthcare products [16]. Group 4: Support Measures - Utilize the city's medical health coordination mechanism to ensure effective service and support for key areas [21]. - Encourage investment from various social capital sources to boost innovation in the healthcare sector [21]. - Attract top scientists and teams to enhance talent cultivation in the AI healthcare field [21].