刚刚！利好来了

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].