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Expert Consensus on Ethical Governance for Clinical Applications of Generative Medical Artificial Intelligence(2025
Meng-Chun Gong1,2, Yong-Hui Ma3, Hui Pan4
1Guangzhou Medical University Women and Children's Medical Center, Guangzhou 511400, China.
Zhongguo Yi Xue Ke Xue Yuan Xue Bao. Acta Academiae Medicinae Sinicae
|February 11, 2026
Summary
Generative medical artificial intelligence (GMAI) offers significant clinical benefits but poses ethical challenges. This consensus establishes a governance framework for GMAI
Area of Science:
- Medical Artificial Intelligence
- Healthcare Ethics
- Clinical Governance
Background:
- Generative medical artificial intelligence (GMAI) is rapidly advancing in healthcare, transforming diagnosis and treatment.
- GMAI applications include diagnostic suggestions, treatment optimization, and enhanced doctor-patient communication.
- Novel ethical challenges arise from GMAI's open-ended nature, including bias, accountability, privacy, and cultural adaptability.
Purpose of the Study:
- To address the lag in ethical governance for GMAI.
- To establish a standardized governance framework for GMAI in clinical practice.
- To provide guidance for ethical review in GMAI research and application within China's context.
Main Methods:
- Assembled a multidisciplinary expert panel (medical ethics, clinical medicine, AI, hospital management, public health, law).
- Utilized a "prevention-control-remediation" governance logic.
- Conducted two rounds of expert consultations integrating international norms and domestic policies.
Main Results:
- Developed a consensus on ethical governance for GMAI.
- Provided a reference for clinical ethical review of GMAI.
- Established an authoritative guidance framework tailored to China's requirements.
Conclusions:
- Ethical governance for GMAI requires a standardized framework to address emerging challenges.
- The developed consensus offers a practical guide for ethical clinical application of GMAI.
- This framework supports responsible innovation and implementation of GMAI in healthcare.
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