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医学研究中生成式人工智能工具使用的报告指南:GAMER声明

Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement.

作者信息

Luo Xufei, Tham Yih Chung, Giuffrè Mauro, Ranisch Robert, Daher Mohammad, Lam Kyle, Eriksen Alexander Viktor, Hsu Che-Wei, Ozaki Akihiko, Moraes Fabio Ynoe de, Khanna Sahil, Su Kuan-Pin, Begagić Emir, Bian Zhaoxiang, Chen Yaolong, Estill Janne

机构信息

Research Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China.

Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

出版信息

BMJ Evid Based Med. 2025 May 13. doi: 10.1136/bmjebm-2025-113825.

Abstract

OBJECTIVES

Generative artificial intelligence (GAI) tools can enhance the quality and efficiency of medical research, but their improper use may result in plagiarism, academic fraud and unreliable findings. Transparent reporting of GAI use is essential, yet existing guidelines from journals and institutions are inconsistent, with no standardised principles.

DESIGN AND SETTING

International online Delphi study.

PARTICIPANTS

International experts in medicine and artificial intelligence.

MAIN OUTCOME MEASURES

The primary outcome measure is the consensus level of the Delphi expert panel on the items of inclusion criteria for GAMER (Rreporting guideline for the use of Generative Artificial intelligence tools in MEdical Research).

RESULTS

The development process included a scoping review, two Delphi rounds and virtual meetings. 51 experts from 26 countries participated in the process (44 in the Delphi survey). The final checklist comprises nine reporting items: general declaration, GAI tool specifications, prompting techniques, tool's role in the study, declaration of new GAI model(s) developed, artificial intelligence-assisted sections in the manuscript, content verification, data privacy and impact on conclusions.

CONCLUSION

GAMER provides universal and standardised guideline for GAI use in medical research, ensuring transparency, integrity and quality.

摘要

目的

生成式人工智能(GAI)工具可提高医学研究的质量和效率,但其不当使用可能导致抄袭、学术欺诈及不可靠的研究结果。对GAI的使用进行透明报告至关重要,但期刊和机构现有的指南并不一致,缺乏标准化原则。

设计与背景

国际在线德尔菲研究。

参与者

医学和人工智能领域的国际专家。

主要结局指标

主要结局指标是德尔菲专家小组对GAMER(医学研究中生成式人工智能工具使用报告指南)纳入标准项目的共识水平。

结果

制定过程包括范围审查、两轮德尔菲调查和虚拟会议。来自26个国家的51名专家参与了该过程(44名参与德尔菲调查)。最终清单包括九个报告项目:一般声明、GAI工具规范、提示技术、工具在研究中的作用、新开发的GAI模型声明、稿件中的人工智能辅助部分、内容验证、数据隐私以及对结论的影响。

结论

GAMER为医学研究中GAI的使用提供了通用且标准化的指南,确保了透明度、完整性和质量。

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