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

Applications of AI (230) Artificial Intelligence (1960) Foundations of AI (56)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44191, first published .
Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study

Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study

Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study

Authors of this article:

Thanai Pongdee1 Author Orcid Image ;   Nicholas B Larson2 Author Orcid Image ;   Rohit Divekar1 Author Orcid Image ;   Suzette J Bielinski3 Author Orcid Image ;   Hongfang Liu4 Author Orcid Image ;   Sungrim Moon4 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Yao M, Huang L, Leventhal E, Sun C, Stephen S, Liou L. Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study. JMIR Medical Education 2025;11:e63602 View
  2. Gogali A, Kyriakopoulos C, Potonos D, Ladias A, Tatsis K, Kostikas K. Artificial Intelligence in Asthma: Current Status, Opportunities, and Pitfalls. The Journal of Allergy and Clinical Immunology: In Practice 2025 View

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  1. Probierz B, Straś A. Intelligent Information and Database Systems. View