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

Artificial Intelligence (1186) Natural Language Processing (636) Machine Learning (1370) Clinical Information and Decision Making (1314) Decision Support for Health Professionals (1127) Electronic Health Records (961) Stroke (147)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22951, first published .
Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation

Authors of this article:

Yiqing Zhao1 Author Orcid Image ;   Sunyang Fu1 Author Orcid Image ;   Suzette J Bielinski1 Author Orcid Image ;   Paul A Decker1 Author Orcid Image ;   Alanna M Chamberlain1 Author Orcid Image ;   Veronique L Roger1 Author Orcid Image ;   Hongfang Liu1 Author Orcid Image ;   Nicholas B Larson1 Author Orcid Image
Article Authors Cited by (15) Tweetations (8) Metrics

Yiqing Zhao   1 , PhD ;   Sunyang Fu   1 , MHI ;   Suzette J Bielinski   1 , PhD ;   Paul A Decker   1 , MSc ;   Alanna M Chamberlain   1 , PhD ;   Veronique L Roger   1 , MD ;   Hongfang Liu   1 , PhD ;   Nicholas B Larson   1 , PhD

1 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States

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