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

Generative Language Models Including ChatGPT (708) AI Language Models in Health Care (202) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (87) Machine Learning (2076)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70080, first published .
Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study

Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study

Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study

Authors of this article:

Han Yang1 Author Orcid Image ;   Mingchen Li2 Author Orcid Image ;   Huixue Zhou1 Author Orcid Image ;   Yongkang Xiao1 Author Orcid Image ;   Qian Fang3 Author Orcid Image ;   Shuang Zhou2 Author Orcid Image ;   Rui Zhang2 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Kurz C, Merzhevich T, Eskofier B, Kather J, Gmeiner B. Benchmarking vision-language models for diagnostics in emergency and critical care settings. npj Digital Medicine 2025;8(1) View
  2. Zhang Y, Xie X, Xu Q. ChatGPT in Medical Education: Bibliometric and Visual Analysis. JMIR Medical Education 2025;11:e72356 View
  3. Liu M, Wang B. Integrating natural non-pharmaceutical therapies into medical tourism: a dynamic health portrait-driven model for proactive older adult health and public health services. Frontiers in Public Health 2025;13 View
  4. Koppula M, Madhulika F, Sreeramoju N, Kolimi P. AI-Powered Chatbot for FDA Drug Labeling Information Retrieval: OpenAI GPT for Grounded Question Answering. Analytics 2025;4(4):33 View
  5. Elshaer Z, Rashed E. CURE: Confidence-Driven Unified Reasoning Ensemble Framework for Medical Question Answering. Big Data and Cognitive Computing 2025;9(12):299 View