Large Language Model Influence on Diagnostic Reasoning A Randomized Clinical Trial

• Published in: JAMA network open Vol. 7; no. 10; p. e2440969
• Main Authors: Goh, Ethan, Gallo, Robert, Hom, Jason, Strong, Eric, Weng, Yingjie, Kerman, Hannah, Cool, Joséphine A., Kanjee, Zahir, Parsons, Andrew S., Ahuja, Neera, Horvitz, Eric, Yang, Daniel, Milstein, Arnold, Olson, Andrew P. J., Rodman, Adam, Chen, Jonathan H.
• Format: Journal Article
• Language: English
• Published: United States American Medical Association 01.10.2024
• Subjects: Adult; Clinical Competence - statistics & numerical data; Clinical Reasoning; Clinical trials; Female; Health Informatics; Humans; Language; Large language models; Male; Multiple choice; Online Only; Original Investigation; Physicians - psychology; Physicians - statistics & numerical data; Single-Blind Method

Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves physician diagnostic reasoning. To assess the effect of an LLM on physicians' diagnostic reas...