Do ChatGPT and Gemini’s Recommendations Align With Established Guidelines for Hand and Upper Extremity Surgery?
Despite modest concordance rates, both models exhibited significant limitations, including variability across topics and guideline strengths, as well as insufficient citation transparency. These findings highlight the challenges in integrating LLMs into clinical practice and emphasize the need for further refinement and evaluation before adoption in hand surgery.
Authors
- Matthew V. Abola (ORCID: https://orcid.org/0000-0001-8084-3515)
- Daniel A. Osei (ORCID: https://orcid.org/0000-0002-1540-8426)
- Yibin B. Zhang (ORCID: https://orcid.org/0000-0003-2546-6790)
- Fielding Fischer (ORCID: https://orcid.org/0000-0002-6994-5120)
- Troy B. Amen (ORCID: https://orcid.org/0000-0003-0792-9739)
- Scott W. Wolfe (ORCID: https://orcid.org/0000-0001-5717-8668)
Institutions
- Hospital for Special Surgery (US)
- Harvard University (US)
Publication Details
- Journal
- Hand
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1177/15589447251371089
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00