Comparative study of the performance of ChatGPT-4, Claude, Gemini, Mistral, and perplexity on multiple-choice questions in cardiology
Despite variations in their performance profiles, these five LLMs studied have relatively similar capabilities for answering well-structured cardiology multiple-choice questions. They could therefore be valuable tools in medical education in our resource-limited context.
Authors
- Patrice Zabsonré
- Rélwendé Aristide Yaméogo (ORCID: https://orcid.org/0000-0003-3291-1100)
- Nobila Valentin Yaméogo (ORCID: https://orcid.org/0000-0003-2791-7882)
- A.K. Samadoulougou
- A. Seghda (ORCID: https://orcid.org/0000-0003-3840-9322)
- Wendlassida Martin Nacanabo (ORCID: https://orcid.org/0009-0002-2047-1830)
- Yannick Laurent Tchenadoyo Bayala (ORCID: https://orcid.org/0009-0004-9095-8948)
- Anna Tall Thiam (ORCID: https://orcid.org/0009-0009-3437-0003)
Institutions
- Université Joseph Ki-Zerbo (BF)
- Centre Hospitalier Universitaire Yalgado Ouédraogo (BF)
Publication Details
- Journal
- BMC Cardiovascular Disorders
- Published
- 2025-12-09
- DOI
- https://doi.org/10.1186/s12872-025-05431-y
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00