Expert consensus on the application and governance of artificial intelligence in medical institutions (2026)

Read full text
Authors: Yanlin Cao, Jing Wang, Jiangjun Wang, Jiangjun Wang, Jiangjun Wang, Zheng Chen, Yuxi Li, Yi Zhang, Guangzhen Zhong, Ping Song, Xing Liu
Cited by: 1
References: 4

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 changes 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, involves 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 that medical institutions should consider during AI implementation and management, 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 and circuit-breaker mechanisms, as well as progressive AI competency training systems. This consensus aims to establish a compliance baseline and development direction for AI applications in medical institutions, characterized by safety, efficacy, fairness, and interpretability, 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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Quality and Safety in Healthcare Ethics and Social Impacts of AI

Publication details

Journal / source
Intelligent Medicine
Publisher
Elsevier BV
Volume
6
Issue
4
Pages
442–447
Publication date
23 May 2026
Language
EN