Artificial Intelligence Clinical Reasoning in Board-Style Clinical Vignettes: A Comparative Study
The findings indicate that current LLMs possess strong potential as supplemental tools for diagnostic reasoning and medical education. Their ability to generate accurate diagnoses from complex clinical scenarios suggests value for training and clinical decision support. However, variability across platforms highlights the need for cautious implementation. Ethical considerations-including algorithmic bias, overreliance on AI-generated outputs, and patient privacy-must be addressed prior to clinical integration. Future research should incorporate larger and more diverse case sets, include specialty-specific assessments, and establish governance frameworks to guide responsible AI use in medical settings.
Authors
- Joseph M. Braun (ORCID: https://orcid.org/0000-0002-5239-3235)
- Kenneth A Quezada
- Nadiya A Persaud
- Ledio Gjunkshi
- Lorela Gjunkshi
Institutions
- Alabama College of Osteopathic Medicine (US)
- Saba University (YE)
Publication Details
- Journal
- Cureus
- Published
- 2025-10-14
- DOI
- https://doi.org/10.7759/cureus.94563
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00