Core Viewpoint - The National Health Commission has released implementation opinions to promote and standardize the application of "Artificial Intelligence + Healthcare," aiming for high-quality development in the health sector by 2027 and 2030 [1][2]. Group 1: Implementation Goals - By 2027, a series of high-quality data sets and trusted data spaces will be established in the health sector, along with the formation of clinical specialty vertical large models and intelligent applications [1][2]. - By 2030, intelligent auxiliary applications for grassroots diagnosis and treatment will achieve full coverage, with secondary hospitals widely adopting AI technologies for medical imaging and clinical decision-making [1][2]. Group 2: Key Applications - Strengthening intelligent applications in grassroots healthcare, focusing on resource-sharing centers for medical imaging, ECG diagnosis, and chronic disease management [3]. - Establishing intelligent auxiliary diagnosis applications for common diseases at the grassroots level, enhancing the diagnostic capabilities of primary care physicians [3]. - Promoting intelligent medical imaging diagnostic services, encouraging hospitals to develop multi-disease applications from single disease models [4][5]. Group 3: Patient Services - Optimizing patient service processes with intelligent appointment scheduling, pre-consultation, and follow-up services to improve patient experience [6]. - Supporting the establishment of intelligent referral information systems to allocate resources effectively based on patient needs and hospital capacities [6]. Group 4: Traditional Chinese Medicine (TCM) - Enhancing intelligent TCM diagnostic applications by building knowledge bases and supporting the development of AI models for TCM [7]. - Promoting intelligent management of traditional Chinese medicine throughout its lifecycle, including cultivation, production, and usage [7]. Group 5: Public Health - Strengthening infectious disease monitoring and early warning systems through AI, providing real-time support for public health decision-making [8]. - Enhancing emergency management and response capabilities in public health through AI applications [8]. Group 6: Research and Education - Promoting intelligent applications in medical research to improve efficiency and quality in various research processes [9]. - Expanding health education services through personalized health knowledge dissemination and innovative knowledge provision for healthcare professionals [9]. Group 7: Industry Governance - Promoting intelligent management in healthcare institutions, focusing on quality, cost management, and resource allocation [11]. - Strengthening regulatory frameworks for AI applications in healthcare, ensuring safety and compliance [15]. Group 8: Health Industry Development - Encouraging the development of new intelligent service models in health consumption, including health management and consultation services [12]. - Supporting innovation in intelligent medical equipment and information technology within the healthcare sector [12]. Group 9: Infrastructure and Data - Building a comprehensive health information platform to connect various healthcare institutions and improve data sharing [13]. - Enhancing the supply of medical data and optimizing data collection processes for better AI application [13]. Group 10: Talent and Standards - Strengthening the training of AI professionals in the health sector and establishing a robust policy framework for AI applications [14]. - Promoting pilot projects to facilitate the practical application of AI in healthcare [16].