医学研究人机融合内容透明披露规范与实施指南(2026年版)OA
Standards and Guidance for Transparent Disclosure of Human-Artificial Intelligence Collaboration Content in Medical Research(2026)
人工智能(AI)工具的快速迭代,正在推动医学研究进入人机融合的新阶段.在这一融合进程中,AI 已从外部工具内化为研究流程的功能性环节,人类研究者与 AI 之间的协作边界日益模糊,治理困境凸显.与此同时,国内外对 AI 辅助内容的发表声明标准尚不统一,存在显著的披露盲区和执行脱节.为此,由中国高校科技期刊研究会医学期刊专业委员会发起,涵盖医学、生物统计学、流行病学、医学伦理学、科技期刊编辑学及医学 AI 技术等领域的多学科专家团队,采用改良德尔菲法,经过3 轮在线问卷调查和2 轮共识会议,基于1 692 种医学期刊的政策调查、国际医学期刊编辑委员会等国际组织立场声明、全球知名学术出版商(Elsevier、Springer Nature、Wiley、Taylor&Francis、SAGE 等)AI政策文本及 AI 检测工具性能比较研究等证据来源,围绕医学出版中的核心问题形成10 条推荐意见.本指南强调"透明披露、人类负责、风险分级、技术辅助"的核心理念,旨在充分获取 AI 技术红利的同时坚守学术诚信底线,为医学研究中人机融合内容的规范声明提供系统性框架,并为研究者、期刊编辑、审稿人及学术机构提供可操作的规范指引.
The rapid iteration of artificial intelligence(AI)tools is propelling medical research into a new phase characterized by human-AI collaboration.In the course of this process,AI has evolved from an exter-nal instrument into a functional component embedded within research workflows.As the collaborative boundary be-tween human researchers and AI becomes increasingly ambiguous,governance challenges have grown increasingly salient.Concurrently,there remains a lack of internationally harmonized standards for the declaration of AI-assis-ted content,giving rise to notable disclosure gaps and implementation disconnects both domestically and abroad.To address these issues,the Professional Committee of Medical Journals of the Society of China University Jour-nals assembled a multidisciplinary expert team covering fields such as medicine,biostatistics,epidemiology,medical ethics,scientific journal editing,and medical AI technology.Employing a modified Delphi method,the team conducted three rounds of online surveys and two consensus meetings.Drawing upon evidence from policy surveys of 1 692 medical journals,position statements from international organizations such as the International Committee of Medical Journal Editors,AI policy texts from the world's major academic publishers(Elsevier,Springer Nature,Wiley,Taylor&Francis,SAGE,etc.),and comparative studies on AI detection tool per-formance,the team ultimately formulated ten recommendations addressing core issues in medical publishing.This guidance emphasizes the core principles of transparent disclosure,human accountability,risk stratification,and technology-assisted oversight,aiming to fully harness the benefits of AI technology while upholding the bottom line of academic integrity.It provides a systematic framework for the standardized disclosure of human-AI collabo-ration content in medical research and offers actionable normative guidance for researchers,journal editors,peer reviewers,and academic institutions.
中国高校科技期刊研究会医学期刊专业委员会;李娜;栾嘉;钱锋
中国医学科学院||北京协和医学院||北京协和医院陆军军医大学扬州大学
医药卫生
人工智能医学研究人机融合透明披露学术诚信出版伦理循证方法学
artificial intelligencemedical researchhuman-artificial intelligence collaborationtransparent disclosureaca-demic integritypublishing ethicsevidence-based methodology
《中国医学科学院学报》 2026 (4)
591-606,16
中国高校医学期刊创新融合发展基金-重点项目(CUJS-YX-2026-01-01)
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