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Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18659, first published .
Woman with hand on neck, experiencing neck pain relief

Characterizing Chronic Pain Episodes in Clinical Text at Two Health Care Systems: Comprehensive Annotation and Corpus Analysis

Characterizing Chronic Pain Episodes in Clinical Text at Two Health Care Systems: Comprehensive Annotation and Corpus Analysis

Journals

  1. Chaturvedi J, Chance N, Mirza L, Vernugopan V, Velupillai S, Stewart R, Roberts A. Development of a Corpus Annotated With Mentions of Pain in Mental Health Records: Natural Language Processing Approach. JMIR Formative Research 2023;7:e45849 View
  2. Dang Y, Li F, Hu X, Keloth V, Zhang M, Fu S, Amith M, Fan J, Du J, Yu E, Liu H, Jiang X, Xu H, Tao C. Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO). Journal of the American Medical Informatics Association 2023;30(9):1465 View
  3. Woodman R, Bryant K, Sorich M, Thompson C, Russell P, Pilotto A, Mangoni A. Phenotyping to predict 12-month health outcomes of older general medicine patients. Aging Clinical and Experimental Research 2025;37(1) View
  4. Keloth V, Selek S, Chen Q, Gilman C, Fu S, Dang Y, Chen X, Hu X, Zhou Y, He H, Fan J, Wang K, Brandt C, Tao C, Liu H, Xu H. Social determinants of health extraction from clinical notes across institutions using large language models. npj Digital Medicine 2025;8(1) View
  5. Kondo U, Ishida M, Masukawa K, Inoue R, Nakayama M, Miyashita M. Quality indicators for cancer pain management: natural language processing and machine learning from electronic clinical records. BMJ Supportive & Palliative Care 2026:spcare-2026-006282 View
  6. Zhang X, Wilson C, Eyre H, Reed II D, Hee Wai T, Kloehn A, Rosser E, Luo G, Zeliadt S. Extraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study. JMIR Research Protocols 2026;15:e96346 View