据上证报报道，8月13日，浙江省卫生健康委员会等10部门印发《浙江省加快推动"人工智能+医疗健 康"高质量发展行动计划》。其中提到，打造多模态医疗行业大模型，建设全自主AI研发框架，形成共 性模型服务能力。开发覆盖医疗服务、健康管理、公共卫生、药械研发、行业治理等一批专病专科模型 和医疗智能体。聚焦人工智能数据与应用、脑机接口、新药创制等领域部署实施重大科技专项，加强多 模态人工智能、具身智能与医学、药学交叉领域的科研布局。鼓励科研机构加强医学人工智能跨学科合 作，形成一批具有全球影响力的科研成果。 另外，8月12日，国家医保局公示通过2025年医保目录及商保创新药目录调整初步形式审查的药品及相 关信息。根据公告，今年共有534个药品通过基本医保目录的形式审查，121个药品通用名通过商保创新 药目录的形式审查，包括定价百万元的抗癌药CAR-T在内，多款高价创新药冲刺商保创新药目录，寻求 创新药多元支付的新途径。 方正证券表示，"人工智能+"驱动医疗产业革命性发展，脑机接口、手术机器人等高端创新设备加速落 地和应用拓展。脑机接口(BCI)商业转化持续加速，受国内监管审批对安全、伦理的高要求，以及产业 发展优先推 ...

Core Insights - The emergence of medical AI agents marks a significant shift in the healthcare industry, transitioning from a focus on large models to intelligent agents that enhance service delivery and operational efficiency [1][2][3] Group 1: Development of Medical AI Agents - The relationship between large models and intelligent agents is characterized by a division of labor, where large models handle cognitive tasks while agents perform actions based on environmental inputs [2] - Medical AI agents are being deployed across various healthcare scenarios, including patient services, diagnostic assistance, hospital management, and even in research and education [3][4] Group 2: Application Scenarios and Key Players - In-hospital applications include patient services, diagnostic assistance, and hospital management, with companies like 惠每科技, 金域医学, and 微医 leading the charge [4] - Out-of-hospital applications feature AI family doctors and health management systems, with key players such as 京东健康 and 平安好医生 [4] - Specialized AI agents are emerging in fields like drug development and insurance claims, with companies like 健康之路 and 中康科技 involved [4] Group 3: Personalization and Specialization - The trend towards personalization in AI agents includes the creation of virtual personas and unique names to enhance user engagement and trust [5][6] - Specialized diagnostic agents are being developed to address specific medical conditions, such as the "腹痛诊疗智能Agent" for abdominal pain management [8][9] Group 4: Challenges and Future Directions - Current medical AI agents are primarily iterative upgrades and have not yet achieved breakthroughs in foundational models [12][14] - The development of specialized agents requires deep involvement from clinical experts to ensure effectiveness and relevance [15] - The advancement of foundational AI capabilities is crucial for the realization of fully functional medical AI agents [16]

Core Insights - The integration of artificial intelligence (AI) in healthcare is transforming the industry by enhancing service quality and efficiency across the entire medical service chain, from early screening to precision treatment and drug development [1] Group 1: AI in Healthcare - AI technology is being utilized to address pain points in primary healthcare, particularly in managing chronic diseases and elderly care, with Shanghai leading the implementation of AI-driven family doctor systems [2][3] - The launch of the "AI Family Doctor" by YaoYing Medical, in collaboration with the Shanghai Artificial Intelligence Laboratory, aims to provide comprehensive healthcare services tailored to individual family members' health profiles [2][3] - Shanghai Telecom and its partners have developed a clinical decision support system for family doctors, integrating AI with authoritative medical knowledge to enhance healthcare delivery [3] Group 2: AI Applications and Innovations - The AI Family Doctor has shown effectiveness in chronic disease management by monitoring key health indicators and providing timely alerts for patient intervention [4][5] - New features such as "shared health records" allow family members to manage health data collectively, promoting intergenerational health management [5] - The introduction of specialized AI models, such as the "CardioMind" for cardiac care, demonstrates the ongoing innovation in AI applications within the healthcare sector [5][6] Group 3: Future of AI in Healthcare - The rapid iteration of multimodal AI models is paving the way for smart hospital construction and clinical decision-making innovations, making AI integration a necessity in healthcare [6] - Future developments in AI healthcare applications are expected to focus on "digital therapeutics," utilizing AI-driven interventions to directly influence patient behavior and health outcomes [6] - The convergence of AI and the health industry is anticipated to create new business models and collaborative innovations across the healthcare ecosystem [6]