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Cited by 97

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

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

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·2025·BMJ Evidence-Based Medicine
DOI 10.1136/bmjebm-2025-113825PMC PMC12703294
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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.

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Research works printed but not linked: 47

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Metadata

Authors
Luo, X., Tham, Y. C., Giuffrè, M., Ranisch, R., Daher, M., Lam, K., Eriksen, A. V., Hsu, C.-W., Ozaki, A., Moraes, F. Y. D., Khanna, S., Su, K.-P., Begagić, E., Bian, Z., Chen, Y., & Estill, J.
Venue
BMJ Evidence-Based Medicine
Publisher
BMJ
Published
2025-05-13
Volume
30
Issue
6
Pages
390-400
ISSN
  • 2515-446X
  • 2515-4478
DOI
10.1136/bmjebm-2025-113825
PMC
PMC12703294
Cited by
97
References
27
Language
en
Licence
creativecommons.org/licenses/by-nc/4.0/ (unspecified)

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CoChat. (2026). Citation check: Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement. https://app.cochat.ai/papers/10.1136/bmjebm-2025-113825
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Luo, X., Tham, Y. C., Giuffrè, M., Ranisch, R., Daher, M., Lam, K., Eriksen, A. V., Hsu, C.-W., Ozaki, A., Moraes, F. Y. D., Khanna, S., Su, K.-P., Begagić, E., Bian, Z., Chen, Y., & Estill, J. (2025). Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement. BMJ Evidence-Based Medicine. https://doi.org/10.1136/bmjebm-2025-113825

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.