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

AI Language Models in Health Care (241) Generative Language Models Including ChatGPT (799) Foundation Models and Their Applications in AI (55) Natural Language Processing (947) Clinical Communication, Electronic Consultation and Telehealth (801) Patient Generated Health Data (19)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62909, first published .
Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study

Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study

Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study

Authors of this article:

Rakhi Asokkumar Subjagouri Nair1 Author Orcid Image ;   Matthias Hartung2 Author Orcid Image ;   Philipp Heinisch1 Author Orcid Image ;   Janik Jaskolski2 Author Orcid Image ;   Cornelius Starke-Knäusel2 Author Orcid Image ;   Susana Veríssimo2 Author Orcid Image ;   David Maria Schmidt1 Author Orcid Image ;   Philipp Cimiano1, 2 Author Orcid Image
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Journals

  1. Cimiano P, Brazda N, Hartung M, Starke-Knäusel C, Schmidt A, De Vuono M, Tyagi A, Gottowik J, Rodriguez-Esteban R, Collins B, Wieckowski K, Escudier T. Best practices for the collection and analysis of patient experience data from social media for patient-focused drug development. Frontiers in Medicine 2026;12 View
  2. Hang Y, Wu J, Bai L, Wu M, Yu J, Li L, Piao X. Evaluation of large Language models on pediatric asthma: a comparative study of Claude3-Opus, Gemini 2.0, ChatGPT-4o, and DeepSeek—a cross-sectional questionnaire study. BMC Medical Informatics and Decision Making 2026;26(1) View

Books/Policy Documents

  1. Boettcher K. 2025 Yearbook Emerging Technologies in Learning. View