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

Research Letter (27) Chatbots and Conversational Agents (740) Generative Language Models Including ChatGPT (708) Artificial Intelligence (2129) Natural Language Processing (917) Development and Evaluation of Research Methods, Instruments and Tools (744) Mobile tools for surgery and perioperative medicine (100) Cross-Sectional Studies in Public Health (431)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56165, first published .
Clinical Accuracy, Relevance, Clarity, and Emotional Sensitivity of Large Language Models to Surgical Patient Questions: Cross-Sectional Study

Clinical Accuracy, Relevance, Clarity, and Emotional Sensitivity of Large Language Models to Surgical Patient Questions: Cross-Sectional Study

Clinical Accuracy, Relevance, Clarity, and Emotional Sensitivity of Large Language Models to Surgical Patient Questions: Cross-Sectional Study

Authors of this article:

Mert Marcel Dagli1 Author Orcid Image ;   Felix Conrad Oettl2, 3 Author Orcid Image ;   Jaskeerat Gujral1 Author Orcid Image ;   Kashish Malhotra4 Author Orcid Image ;   Yohannes Ghenbot1 Author Orcid Image ;   Jang W Yoon1 Author Orcid Image ;   Ali K Ozturk1 Author Orcid Image ;   William C Welch1 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

Journals

  1. Brin D, Sorin V, Konen E, Nadkarni G, Glicksberg B, Klang E. How GPT models perform on the United States medical licensing examination: a systematic review. Discover Applied Sciences 2024;6(10) View
  2. Dagli M, Ghenbot Y, Ahmad H, Chauhan D, Turlip R, Wang P, Welch W, Ozturk A, Yoon J. Development and validation of a novel AI framework using NLP with LLM integration for relevant clinical data extraction through automated chart review. Scientific Reports 2024;14(1) View
  3. Mahamid A, Laver L, Zahalka S, Oettl F, Behrbalk E, Hirschmann M, Samuelsson K. Editorial – Current capacities and future possibilities of large language models in orthopaedic surgery. Journal of Experimental Orthopaedics 2025;12(2) View
  4. Wang C, Zhu Y, Zhang X, Chen X, Li Y, Tan Y, Qi H. Areas of research focus and trends in the research on the application of AIGC in healthcare. Journal of Health, Population and Nutrition 2025;44(1) View
  5. Masur L, Driller M, Suppiah H, Matzka M, Sperlich B, Düking P. Assessment of Recommendations Provided to Athletes Regarding Sleep Education by GPT-4o and Google Gemini: Comparative Evaluation Study. JMIR Formative Research 2025;9:e71358 View
  6. Griffin A, Javier S, Golding M, Runnels T, Matthias M, Shimada S, Higgins D, Zulman D, Midboe A. Designing Patient-Friendly Messages: Tutorial on Applying Human-Centered, Self-Determination Theory With AI Considerations. Journal of Medical Internet Research 2025;27:e78173 View
  7. Oettl F, Pruneski J, Zsidai B, Yu Y, Cong T, Tischer T, Hirschmann M, Samuelsson K. Is orthopaedics entering the age of generative AI?—A narrative review of current applications, challenges, and future directions. Knee Surgery, Sports Traumatology, Arthroscopy 2025 View
  8. Nuccetelli F, Gabellone V, Marsano F, Giovanetti F, Dri P, Valetto M, Prato R. The use of artificial intelligence in healthcare as perceived by the citizens and patients: a narrative review of the literature. European Journal of Public Health 2025 View
  9. Ahmadov N, Muradova A. ChatGPT and deepseek in head and neck cancers: objective scales could strengthen AI research in medicine. European Archives of Oto-Rhino-Laryngology 2025 View