Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks

In this simulated assessment, GPT-4o demonstrated diagnostic biases toward rare conditions and differed substantially from normative probabilistic models and physician practice patterns. These discrepancies could lead to unnecessary over-triage and resource utilization. Integrating LLMs within more rigorous probabilistic frameworks and calibrating them to realistic disease prevalences may be essential for effectively harnessing their potential as clinical decision-support tools.

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Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2026-02-24
DOI
https://doi.org/10.1186/s12911-026-03381-9
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks

David Chartash, D. Wright, Alaa Alashi, Vimig Socrates et al.
BMC Medical Informatics and Decision Making
Machine Learning in Healthcare
article

Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks

David Chartash, D. Wright, Alaa Alashi, Vimig Socrates, Kent McCann, Thomas Huang, R. Andrew Taylor, Conrad W. Safranek
article en

Abstract

In this simulated assessment, GPT-4o demonstrated diagnostic biases toward rare conditions and differed substantially from normative probabilistic models and physician practice patterns. These discrepancies could lead to unnecessary over-triage and resource utilization. Integrating LLMs within more rigorous probabilistic frameworks and calibrating them to realistic disease prevalences may be essential for effectively harnessing their potential as clinical decision-support tools.

BMC Medical Informatics and Decision Making
Yale University (US), Yale New Haven Health System (US), University of Virginia (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 49%
Machine Learning in Healthcare
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