This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (414) Artificial Intelligence (1603) Clinical Information and Decision Making (1548) Decision Support for Health Professionals (1288) Research Instruments, Questionnaires, and Tools (632) Machine Learning (1627) Simulation (125) Data Science (296) Chatbots and Conversational Agents (589) Clinical Information and Decision Making (42) Validity, Reliability, and Bias (97) Theoretical Frameworks and Concepts (284) Case Report (10)

Published on in Vol 26 (2024)

This is a member publication of National University of Singapore

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59439, first published .
Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study

Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study

Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study

Authors of this article:

Yuhe Ke1, 2 Author Orcid Image ;   Rui Yang1 Author Orcid Image ;   Sui An Lie2 Author Orcid Image ;   Taylor Xin Yi Lim2 Author Orcid Image ;   Yilin Ning1 Author Orcid Image ;   Irene Li3 Author Orcid Image ;   Hairil Rizal Abdullah2 Author Orcid Image ;   Daniel Shu Wei Ting1, 4 Author Orcid Image ;   Nan Liu1, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (30) Metrics

Journals

  1. Bousquet C, Beltramin D. Advantages and Inconveniences of a Multi-Agent Large Language Model System to Mitigate Cognitive Biases in Diagnostic Challenges. Journal of Medical Internet Research 2025;27:e69742 View
  2. Yang R, Ning Y, Keppo E, Liu M, Hong C, Bitterman D, Ong J, Ting D, Liu N. Retrieval-augmented generation for generative artificial intelligence in health care. npj Health Systems 2025;2(1) View
  3. Kim S, Schramm S, Adams L, Braren R, Bressem K, Keicher M, Platzek P, Paprottka K, Zimmer C, Hedderich D, Wiestler B. Benchmarking the diagnostic performance of open source LLMs in 1933 Eurorad case reports. npj Digital Medicine 2025;8(1) View