Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/37962
Appears in Collections:Faculty of Health Sciences and Sport Journal Articles
Peer Review Status: Refereed
Title: Cognitive bias in clinical large language models
Author(s): Mahajan, Arjun
Obermeyer, Ziad
Daneshjou, Roxana
Lester, Jenna
Powell, Dylan
Contact Email: dylan.powell@stir.ac.uk
Issue Date: 10-Jul-2025
Date Deposited: 23-Mar-2026
Citation: Mahajan A, Obermeyer Z, Daneshjou R, Lester J & Powell D (2025) Cognitive bias in clinical large language models. <i>npj Digital Medicine</i>, 8, Art. No.: 428. https://doi.org/10.1038/s41746-025-01790-0
Abstract: First Paragraph - Cognitive bias accounts for a significant portion of preventable errors in healthcare, contributing to significant patient morbidity and mortality each year. As large language models (LLMs) are introduced into healthcare and clinical decision-making, these systems are at risk of inheriting – and even amplifying – these existing biases. This article explores both the cognitive biases impacting LLM-assisted medicine and the countervailing strengths these technologies bring to addressing these limitations.
DOI Link: 10.1038/s41746-025-01790-0
Rights: This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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