Abstract
The deep integration of artificial intelligence (AI) in the healthcare sector is revolutionizing medical services, clinical decision-making, and academic research and education in medical institutions. However, its autonomous evolutionary characteristics based on continuous learning and iterative updates pose fundamental challenges to traditional, static regulatory frameworks of medical devices. The “Expert consensus on the application and governance of artificial intelligence in medical institutions (2026),” developed by over 40 leading Chinese medical and scientific research institutions, involved experts from fields such as medicine, hospital management, medical informatics, health policy, law, and medical ethics. Drawing on the latest Chinese and international regulations and best practices, the expert panel systematically compiled a comprehensive governance guide for AI applications across the entire lifecycle of medical institutions, focusing on six thematic pillars: Access evaluation, clinical application, patient rights protection, data governance, risk management, and competency enhancement. For each domain, the consensus details critical factors, including tiered access, multidisciplinary review, real-world validation, cross-validation of competing algorithms, delineation of human-machine collaboration liabilities, tiered informed consent, algorithmic traceability and explainability, dynamic risk monitoring, circuit-breaker mechanisms, and progressive AI competency training systems, that medical institutions should consider during AI implementation and management. This consensus aims to establish a compliance baseline and development direction for AI applications in medical institutions that is characterized by safety, efficacy, fairness, and interpretability, thereby ensuring that technological evolution remains within a legally and ethically sound framework. Ultimately, it serves to promote equitable access to high-quality medical resources and achieve substantial improvements in national health standards.