Bias Sensitivity in Diagnostic Decision-Making: Comparing ChatGPT with Residents.

ABSTRACT:

Background

Diagnostic errors, often due to biases in clinical reasoning, significantly affect patient care. While artificial intelligence chatbots like ChatGPT could help mitigate such biases, their potential susceptibility to biases is unknown.

Methods

This study evaluated diagnostic accuracy of ChatGPT against the performance of 265 medical residents in five previously published experiments aimed at inducing bias. The residents worked in several major teaching hospitals in the Netherlands. The biases studied were case-intrinsic (presence of salient distracting findings in the patient history, effects of disruptive patient behaviors) and situational (prior availability of a look-alike patient). ChatGPT's accuracy in identifying the most-likely diagnosis was measured.

Res

SUBMITTER: Schmidt HG 

PROVIDER: S-EPMC11914423 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature