Accessibility settings

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

Non-randomized Protocols and Methods (ehealth) (1122) Methods and Feasibility Studies (773) Natural Language Processing (1322) Electronic Health Records (1782) Machine Learning (3314) AI Language Models in Health Care (810)

Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/96346, first published .
Doctor discusses shoulder pain with a male patient during a medical consultation.

Extraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study

Extraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study

Authors of this article:

Xiaoyi Zhang1 Author Orcid Image ;   Christopher R Wilson2 Author Orcid Image ;   Hannah Eyre2 Author Orcid Image ;   David E Reed II2, 3 Author Orcid Image ;   Travis Y Hee Wai2 Author Orcid Image ;   Alexander Kloehn2 Author Orcid Image ;   Ethan W Rosser2 Author Orcid Image ;   Gang Luo1 Author Orcid Image ;   Steven B Zeliadt2, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Xiaoyi Zhang   1 , MS ;   Christopher R Wilson   2 , MS ;   Hannah Eyre   2 , MS ;   David E Reed II   2, 3 , PhD ;   Travis Y Hee Wai   2 , PhD ;   Alexander Kloehn   2 , MPH ;   Ethan W Rosser   2 , PhD ;   Gang Luo   1 , PhD ;   Steven B Zeliadt   2, 4 , MPH, PhD

1 Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States

2 Seattle-Denver Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, United States

3 Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States

4 Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, United States

Corresponding Author:

  • Steven B Zeliadt, MPH, PhD
  • Seattle-Denver Center of Innovation for Veteran-Centered and Value-Driven Care
  • VA Puget Sound Health Care System
  • 1660 S. Columbian Way
  • Seattle, WA 98108
  • United States
  • Phone: 1 2062774175
  • Email: steven.zeliadt@va.gov