Artificial intelligence chain-of-thought reasoning in nuanced medical scenarios: mitigation of cognitive biases through model intransigence

Some biases persist in chain-of-thought reasoning LLMs, and models tend to produce intransigent recommendations. These findings highlight the role of clinicians to think broadly, respect diversity and remain vigilant when interpreting chain-of-thought reasoning artificial intelligence LLMs in nuanced medical decisions for patients.

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Publication Details

Journal
BMJ Quality & Safety
Published
2025-11-24
DOI
https://doi.org/10.1136/bmjqs-2025-019299
Primary Topic
Clinical Reasoning and Diagnostic Skills
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence chain-of-thought reasoning in nuanced medical scenarios: mitigation of cognitive biases through model intransigence

Donald A. Redelmeier, Jonathan Wang
BMJ Quality & Safety
Clinical Reasoning and Diagnostic Skills
article

Artificial intelligence chain-of-thought reasoning in nuanced medical scenarios: mitigation of cognitive biases through model intransigence

Donald A. Redelmeier, Jonathan Wang
article en

Abstract

Some biases persist in chain-of-thought reasoning LLMs, and models tend to produce intransigent recommendations. These findings highlight the role of clinicians to think broadly, respect diversity and remain vigilant when interpreting chain-of-thought reasoning artificial intelligence LLMs in nuanced medical decisions for patients.

BMJ Quality & Safety
Sunnybrook Health Science Centre (CA), University of Toronto (CA), Health Sciences Centre (CA)
Openalex Percentile: Top 58%
Clinical Reasoning and Diagnostic Skills
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