Core Insights - The National Health Commission and five other departments have jointly issued implementation opinions to promote and regulate the application of "Artificial Intelligence + Healthcare" [1] - By 2027, the goal is to establish high-quality health industry data sets and trusted data spaces, along with the widespread application of intelligent decision-making and patient service systems in healthcare institutions [1] Group 1: Clinical Diagnosis - The implementation opinions emphasize the promotion of intelligent diagnostic services in medical imaging, supporting the collective development of AI-assisted diagnosis and report generation in provincial hospitals [2] - There is a focus on enhancing diagnostic efficiency and report quality by expanding AI-assisted diagnosis from single diseases to multiple diseases affecting single organs [2] - High-level hospitals are encouraged to gather and develop high-quality medical imaging data for AI model research and upgrades [2] Group 2: Health Industry Development - The implementation opinions support collaboration between medical equipment manufacturers and healthcare institutions to advance intelligent medical equipment development [2] - Key areas for intelligent upgrades include medical imaging, diagnostic testing, treatment, monitoring, and life support equipment [2] - There is encouragement for the application of domestically produced intelligent medical equipment in healthcare institutions, particularly for innovative tasks in AI medical devices [2]

Core Viewpoint - The National Health Commission and five other departments have jointly issued implementation opinions to promote and regulate the application of "Artificial Intelligence + Healthcare," aiming for significant advancements in medical imaging and intelligent healthcare services by 2027 [1][2]. Group 1: Implementation Goals - By 2027, a number of high-quality health industry data sets and credible data spaces will be established, along with the development of specialized clinical models and intelligent applications [1]. - The implementation opinions emphasize the widespread application of intelligent auxiliary decision-making in grassroots diagnosis, specialized clinical treatment, and patient services within healthcare institutions [1]. Group 2: Key Application Areas - The opinions outline 24 key applications across eight areas, including grassroots applications, clinical diagnosis, patient services, and traditional Chinese medicine [1]. - There is a focus on enhancing infrastructure, enriching medical data supply, optimizing AI algorithms, strengthening pilot base construction, and supporting technology talent and standards [1]. Group 3: Clinical Diagnosis and Health Industry - The promotion of intelligent diagnostic services in medical imaging is highlighted, with support for centralized provincial efforts in AI-assisted diagnosis, report generation, and treatment recommendations [2]. - The opinions encourage collaboration between medical equipment manufacturers and healthcare institutions to drive intelligent upgrades in medical devices, particularly in imaging, diagnostics, treatment, and monitoring [2].

Core Insights - The National Health Commission and five other departments have jointly released implementation opinions to promote and regulate the application of "Artificial Intelligence + Healthcare" [1][2] - By 2027, the goal is to establish high-quality data sets and trusted data spaces in the healthcare sector, along with the development of clinical specialty models and intelligent applications [1] - The implementation opinions emphasize the need for AI applications in eight key areas, including grassroots applications, clinical diagnosis, patient services, and traditional Chinese medicine [1] Group 1: Clinical Diagnosis - The implementation opinions propose the promotion of intelligent diagnostic services in medical imaging, supporting the centralized and coordinated development of AI-assisted diagnosis and report generation [2] - Encouragement is given for secondary and higher-level hospitals to expand AI-assisted diagnosis from single disease types to multiple diseases affecting single organs, enhancing diagnostic efficiency and report quality [2] - High-level hospitals are to be selected for high-quality medical imaging data aggregation and application research, supporting the development and iterative upgrade of AI large models [2] Group 2: Health Industry - The implementation opinions support medical equipment manufacturers in collaborating with healthcare institutions and research institutes to conduct R&D on intelligent medical equipment [2] - Focus areas include the intelligent upgrade of medical equipment in imaging, diagnostic testing, treatment, monitoring, and life support [2] - There is encouragement for joint applications to participate in innovative tasks for AI medical devices, particularly for domestically produced intelligent medical equipment in its first application at healthcare institutions [2]

Core Viewpoint - The article outlines the implementation opinions on promoting and regulating the application of "Artificial Intelligence + Healthcare," aiming to enhance the quality of healthcare services through AI integration by 2027 and 2030 [2][21]. Overall Requirements - The guiding ideology emphasizes government guidance, multi-party participation, innovation-driven, and safety control principles to promote the standardized application of AI in healthcare, meeting the growing health service demands of the public [3][20]. - By 2027, a high-quality dataset and trusted data space in the healthcare sector will be established, with widespread application of AI-assisted decision-making in clinical specialties and patient services [4][25]. Key Application Areas - **AI + Grassroots Applications**: Focus on enhancing intelligent applications in community healthcare, including intelligent diagnostic support for common diseases and chronic disease management [5][6]. - **AI + Clinical Diagnosis**: Promotion of intelligent diagnostic services in medical imaging and clinical decision support for specialized diseases [6][7]. - **AI + Patient Services**: Optimization of patient service processes through intelligent appointment systems and referral services [7][8]. - **AI + Traditional Chinese Medicine**: Development of intelligent applications in TCM diagnosis and management of herbal medicine [8][9]. - **AI + Public Health**: Strengthening infectious disease monitoring and emergency management through AI applications [9][10]. - **AI + Research and Education**: Enhancing medical research efficiency and expanding health education services through intelligent applications [11][12]. - **AI + Industry Governance**: Promoting intelligent management in healthcare institutions and enhancing regulatory frameworks [12][13]. - **AI + Health Industry**: Encouraging the development of new service models and innovative medical equipment through AI [13][14]. Strengthening Application Foundations - **Infrastructure Development**: Establishing a nationwide health information platform to connect all healthcare institutions [14][32]. - **Data Supply Enhancement**: Promoting data sharing across departments and optimizing data collection processes [14][33]. - **AI Algorithm Optimization**: Supporting the establishment of public service platforms for AI computational power [14][35]. - **Pilot Base Construction**: Building national AI application pilot bases to support various healthcare applications [14][37]. - **Talent and Standards Support**: Strengthening the training of AI professionals and establishing relevant policies and ethical guidelines [15][39]. Regulatory Safety Standards - **Industry Management Optimization**: Improving the governance mechanism for AI applications in healthcare [16][40]. - **Innovative Regulatory Approaches**: Establishing monitoring and evaluation systems for AI applications to ensure safety and privacy [16][41]. - **Data Security and Privacy Protection**: Enhancing security measures for healthcare data and personal information [16][41]. Organizational Support - **Institutional Development**: Encouraging local governments to strengthen AI research support and establish funding mechanisms [17][41]. - **Pilot Demonstrations**: Utilizing AI application pilot bases to promote high-quality data collection and sharing [17][42]. - **Public Awareness and Cooperation**: Enhancing policy promotion and international cooperation in AI applications [17][42].

Core Viewpoint - The article discusses the implementation opinions on promoting and regulating the application of "Artificial Intelligence + Healthcare" in China, outlining a strategic framework for the development of AI in the healthcare sector by 2027 and 2030 [1][4]. Group 1: Overall Requirements - The guiding ideology emphasizes government guidance, multi-party participation, innovation-driven approaches, and safety control, aiming to meet the growing health service demands of the public [7]. - By 2027, the goal is to establish high-quality datasets and trusted data spaces in the healthcare sector, with widespread applications of AI in clinical decision-making and patient services [7][8]. - By 2030, the aim is for comprehensive coverage of intelligent assistance in grassroots diagnosis and the establishment of a standard system for AI applications in healthcare [8]. Group 2: Deepening Key Applications - AI applications will focus on eight areas, including grassroots healthcare, clinical diagnosis, patient services, traditional Chinese medicine, public health, scientific research, industry governance, and health industry development [9][10][11][12]. - Specific initiatives include enhancing intelligent applications in community healthcare, promoting intelligent diagnostic services in medical imaging, and improving management of chronic diseases [9][10]. Group 3: Strengthening Application Foundations - Emphasis on infrastructure development, including the construction of a national health information platform connecting all healthcare institutions [14]. - The article highlights the need for rich medical data supply and optimized AI algorithms, as well as the establishment of comprehensive co-creation platforms for AI applications [15][16]. Group 4: Regulating Safety and Supervision - Proposals include optimizing industry management and review systems, innovating regulatory methods, and enhancing data security and personal privacy protection [17]. Group 5: Strengthening Organizational Support - The article calls for improved institutional frameworks, pilot demonstrations, and collaborative promotion of AI in healthcare to ensure mutual benefits and shared outcomes [17].

Core Viewpoint - The implementation of the "Artificial Intelligence + Healthcare" initiative aims to enhance the quality of healthcare services through the integration of advanced AI technologies, with specific goals set for 2027 and 2030 [1][5][31]. Summary by Sections Overall Requirements - The initiative is guided by Xi Jinping's thought and aims to promote the standardized application of AI in healthcare, enhancing service capabilities and optimizing resource allocation to meet the growing health service demands of the public by 2027 and 2030 [31][41]. Key Applications - Emphasis on grassroots applications, focusing on enhancing diagnostic and treatment capabilities at the community level, including the establishment of intelligent diagnostic applications for common diseases [32][33]. - Promotion of AI in clinical diagnosis, particularly in medical imaging and specialized disease treatment, to improve diagnostic efficiency and quality [33][34]. - Development of patient services through AI, including optimized patient flow and intelligent referral systems to enhance the overall patient experience [34][35]. Infrastructure and Data - Establishment of high-quality healthcare data sets and trusted data spaces by 2027, with a focus on creating a national AI application pilot base in healthcare [31][41]. - Strengthening of health information platforms to ensure comprehensive data sharing and integration across healthcare institutions [41][42]. Safety and Regulation - Implementation of a comprehensive governance mechanism for AI applications in healthcare, focusing on data security and personal privacy protection [43][44]. - Development of innovative regulatory methods and early warning mechanisms to monitor AI applications in healthcare [43][44]. Organizational Support - Encouragement of local governments to enhance AI research support, talent evaluation mechanisms, and funding for AI initiatives in healthcare [44]. - Promotion of pilot projects to build high-quality data sets and trusted data spaces, facilitating the practical application of AI technologies in healthcare [44].