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

Digital Pain Assessment and Management (232) Machine Learning (2076) Generative Language Models Including ChatGPT (708) Research Instruments, Questionnaires, and Tools (738) Methods and Instruments in Medical Informatics (189)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65903, first published .
Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation

Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation

Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation

Authors of this article:

Jacopo Amidei1 Author Orcid Image ;   Rubén Nieto2 Author Orcid Image ;   Andreas Kaltenbrunner1 Author Orcid Image ;   Jose Gregorio Ferreira De Sá1 Author Orcid Image ;   Mayte Serrat3, 4 Author Orcid Image ;   Klara Albajes5 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Li F, Hu C, Luo X. Research status, hotspots and perspectives of artificial intelligence applied to pain management: a bibliometric and visual analysis. Updates in Surgery 2025 View
  2. Chan A, Knitza J, Venerito V, Gupta L, Richter J, Hamann P, Hans D, Krusche M, van den Bempt B, van Laar J, Blanchard M, Hügle T. Five years of the Digital Rheumatology Network: insights and future directions. EULAR Rheumatology Open 2025;1(3):89 View
  3. Ozek B, Lu Z, Radhakrishnan S, Kamarthi S. Influence of Pre-Existing Pain on the Body’s Response to External Pain Stimuli: Experimental Study. JMIR Biomedical Engineering 2025;10:e70938 View
  4. Kuculmez O, Usen A, Ahi E. Referential hallucination and clinical reliability in large language models: a comparative analysis using regenerative medicine guidelines for chronic pain. Rheumatology International 2025;45(10) View
  5. Norel R, Gewandter J, Zhang Z, Tahsin A, Abdallah C, Markman J, Duan Z, Cecchi G, Geha P. Turning Patients’ Open-Ended Narratives of Chronic Pain Into Quantitative Measures: Natural Language Processing Study. JMIR Human Factors 2025;12:e80269 View