Comparative analysis of large language models in clinical diagnosis: performance evaluation across common and complex medical cases
Leading LLMs show remarkable diagnostic accuracy in diverse clinical cases. To fully realize their potential for improving patient care, we must now focus on creating practical implementation frameworks and translational research to integrate these powerful AI tools into medicine.
Authors
- Furkan Bahar (ORCID: https://orcid.org/0000-0002-4672-5977)
- Ali Emre Bardak (ORCID: https://orcid.org/0000-0002-3073-8538)
- Craig Noronha (ORCID: https://orcid.org/0000-0002-9063-2903)
- Taha Dinç (ORCID: https://orcid.org/0000-0002-7759-6135)
Institutions
- Boston Medical Center (US)
- Mount Auburn Hospital (US)
- Harvard University (US)
- St. Elizabeth's Medical Center (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf055
- Citations
- 14
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 9.16