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

Artificial Intelligence (2459) Public (e)Health, Digital Epidemiology and Public Health Informatics (1151) Natural Language Processing (995) Electronic Health Records (1421) Public Health Informatics (155) Secondary Use of Clinical Data for Research and Surveillance (504) Machine Learning (2308) Stroke (277) Cardiac Arrhythmia, Atrial Fibrillation (117)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28946, first published .
Futuristic medical interface showing patient data, ECG, brain scan, and network analysis.

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Authors of this article:

Peter L Elkin1, 2, 3 Author Orcid Image ;   Sarah Mullin1 Author Orcid Image ;   Jack Mardekian4 Author Orcid Image ;   Christopher Crowner1 Author Orcid Image ;   Sylvester Sakilay1 Author Orcid Image ;   Shyamashree Sinha1 Author Orcid Image ;   Gary Brady4 Author Orcid Image ;   Marcia Wright4 Author Orcid Image ;   Kimberly Nolen4 Author Orcid Image ;   JoAnn Trainer4 Author Orcid Image ;   Ross Koppel1 Author Orcid Image ;   Daniel Schlegel1 Author Orcid Image ;   Sashank Kaushik1 Author Orcid Image ;   Jane Zhao1 Author Orcid Image ;   Buer Song1 Author Orcid Image ;   Edwin Anand1 Author Orcid Image
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