Assessing the methodologic quality of systematic reviews using generative large language models
GPT showed promising ability to efficiently and accurately assess the quality of SRs in urology.
Authors
- Philipp Dahm (ORCID: https://orcid.org/0000-0003-2819-2553)
- Carly D. Miller (ORCID: https://orcid.org/0009-0008-7609-0782)
- Bowen Yao (ORCID: https://orcid.org/0000-0002-6165-0379)
- Onuralp Ergun (ORCID: https://orcid.org/0000-0001-6433-4534)
- Vikram M. Narayan (ORCID: https://orcid.org/0000-0003-3731-4209)
- Maylynn Ding
Institutions
- University of Minnesota (US)
- Emory University (US)
- Minneapolis VA Health Care System (US)
- Minneapolis VA Medical Center (US)
- McMaster University (CA)
Publication Details
- Journal
- Canadian Urological Association Journal
- Published
- 2025-08-28
- DOI
- https://doi.org/10.5489/cuaj.9243
- Primary Topic
- Meta-analysis and systematic reviews
- Type
- article
- Field-Weighted Citation Impact
- 0.00