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

Natural Language Processing (29) Artificial Intelligence (122) Artificial Intelligence (1215) Machine Learning (1401) Natural Language Processing (650) Respiratory Medicine (64)

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 (1) Tweetations (2) Metrics

Thanai Pongdee   1 , MD ;   Nicholas B Larson   2 , MS, PhD ;   Rohit Divekar   1 , MBBS, PhD ;   Suzette J Bielinski   3 , PhD ;   Hongfang Liu   4 , PhD ;   Sungrim Moon   4 , PhD

1 Division of Allergic Diseases, Mayo Clinic, Rochester, MN, United States

2 Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States

3 Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States

4 Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States

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