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.

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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
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article

Artificial Intelligence Clinical Reasoning in Board-Style Clinical Vignettes: A Comparative Study

Joseph M. Braun, Kenneth A Quezada, Nadiya A Persaud, Ledio Gjunkshi et al.
Cureus
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence Clinical Reasoning in Board-Style Clinical Vignettes: A Comparative Study

Joseph M. Braun, Kenneth A Quezada, Nadiya A Persaud, Ledio Gjunkshi, Lorela Gjunkshi
article en

Abstract

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.

CureusVol. 17(10)
Alabama College of Osteopathic Medicine (US), Saba University (YE)
Openalex Percentile: Top 79%
Artificial Intelligence in Healthcare and Education
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