Expert Consensus on Ethical Governance for Clinical Applications of Generative Medical Artificial Intelligence(2025 Edition).

The research and innovative applications of generative medical artificial intelligence(GMAI)are rapidly advancing in the healthcare field.Significant breakthroughs of GMAI have been achieved in areas such as generating diagnostic suggestions,optimizing treatment plans,and assisting doctor-patient communication,profoundly reshaping the paradigm of clinical diagnosis and treatment.However,the open-ended nature of GMAI's generation raises novel ethical challenges,including algorithmic bias,ambiguous accountability,data privacy breaches,and insufficient cultural adaptability.Current ethical governance lags behind technological implementation,necessitating the establishment of a standardized governance framework.Our research team assembled a multidisciplinary panel of experts spanning medical ethics,clinical medicine,medical artificial intelligence,hospital management,public health,and law.According to the governance logic of "prevention-control-remediation" and integrating international norms with domestic policies,this consensus was developed through two rounds of expert consultation to unify opinions and perspectives.It aims to provide a reference for the specific practice of clinical ethical review in the research and clinical application of GMAI and to establish an authoritative guidance framework for the clinical ethical governance of GMAI,tailored to China's cultural context and national requirements.

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Publication Details

Journal
PubMed
Published
2026-02-01
DOI
https://doi.org/10.3881/j.issn.1000-503x.17220
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Expert Consensus on Ethical Governance for Clinical Applications of Generative Medical Artificial Intelligence(2025 Edition).

Kai Gong, Yun Zhou, Hua Bai, Hui Dai et al.
PubMed
Artificial Intelligence in Healthcare and Education
article

Expert Consensus on Ethical Governance for Clinical Applications of Generative Medical Artificial Intelligence(2025 Edition).

Kai Gong, Yun Zhou, Hua Bai, Hui Dai, Yan Luo, Xun-Ming Ji, Bo-Han Zhang, Yong-Hui Ma, Zhi-Rong Zeng, Hui Pan, Hao Wu, Meng-Chun Gong, Zi-Hao Ouyang, Wei Chen, Hui Liu
article en

Abstract

The research and innovative applications of generative medical artificial intelligence(GMAI)are rapidly advancing in the healthcare field.Significant breakthroughs of GMAI have been achieved in areas such as generating diagnostic suggestions,optimizing treatment plans,and assisting doctor-patient communication,profoundly reshaping the paradigm of clinical diagnosis and treatment.However,the open-ended nature of GMAI's generation raises novel ethical challenges,including algorithmic bias,ambiguous accountability,data privacy breaches,and insufficient cultural adaptability.Current ethical governance lags behind technological implementation,necessitating the establishment of a standardized governance framework.Our research team assembled a multidisciplinary panel of experts spanning medical ethics,clinical medicine,medical artificial intelligence,hospital management,public health,and law.According to the governance logic of "prevention-control-remediation" and integrating international norms with domestic policies,this consensus was developed through two rounds of expert consultation to unify opinions and perspectives.It aims to provide a reference for the specific practice of clinical ethical review in the research and clinical application of GMAI and to establish an authoritative guidance framework for the clinical ethical governance of GMAI,tailored to China's cultural context and national requirements.

PubMedVol. 48(1)
Sun Yat-sen University (CN), Guangdong Medical College (CN), Shanxi Medical University (CN), Xiamen University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking Union Medical College Hospital (CN), Shaoguan University (CN), Ganzhou People's Hospital (CN), Guangzhou Women and Children Medical Center (CN), First Hospital of Shanxi Medical University (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), Xiamen University of Technology (CN), Fuzhou University (CN), Chongqing Medical University (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 61%
Artificial Intelligence in Healthcare and Education
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