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

Foundations of AI (57) Natural Language Processing (879) Applications of AI (260) Machine Learning (2008) Clinical Information and Decision Making (1845) Respiratory Medicine (147)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69132, first published .
Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study

Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study

Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study

Authors of this article:

Fagen Xie1 Author Orcid Image ;   Robert S Zeiger2, 3 Author Orcid Image ;   Mary Marycania Saparudin1 Author Orcid Image ;   Sahar Al-Salman1 Author Orcid Image ;   Eric Puttock1 Author Orcid Image ;   William Crawford4 Author Orcid Image ;   Michael Schatz2, 3 Author Orcid Image ;   Stanley Xu1 Author Orcid Image ;   William M Vollmer5 Author Orcid Image ;   Wansu Chen1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Osman Mohmed F, Osman Homaida W, Babkir Abd Alla Y, Elahdab Hassan R, Mahmoud Ali S, Elfaki Ahmed G, Al Balal Abdelbagi E, Sidahmed Elsaid M. Artificial Intelligence Applications in the Prediction and Management of Pediatric Asthma Exacerbation: A Systematic Review. Cureus 2025 View
  2. van Breugel M, Greenhawt M, Eguiluz-Gracia I, Torres Jaén M, Anagnostou A, Koppelman G. Artificial intelligence in allergy and immunology: Recent developments, implementation challenges, and the road toward clinical impact. Journal of Allergy and Clinical Immunology 2025 View