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

Machine Learning (1505) Clinical Information and Decision Making (1438) Decision Support for Health Professionals (1211) Cardiac Arrhythmia, Atrial Fibrillation (87) Electronic Health Records (1071) Clinical Informatics (1050)

Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29225, first published .
Machine Learning Methodologies for Prediction of Rhythm-Control Strategy in Patients Diagnosed With Atrial Fibrillation: Observational, Retrospective, Case-Control Study

Machine Learning Methodologies for Prediction of Rhythm-Control Strategy in Patients Diagnosed With Atrial Fibrillation: Observational, Retrospective, Case-Control Study

Machine Learning Methodologies for Prediction of Rhythm-Control Strategy in Patients Diagnosed With Atrial Fibrillation: Observational, Retrospective, Case-Control Study

Authors of this article:

Rachel S Kim1 Author Orcid Image ;   Steven Simon2 Author Orcid Image ;   Brett Powers1 Author Orcid Image ;   Amneet Sandhu3 Author Orcid Image ;   Jose Sanchez3 Author Orcid Image ;   Ryan T Borne3 Author Orcid Image ;   Alexis Tumolo3 Author Orcid Image ;   Matthew Zipse3 Author Orcid Image ;   J Jason West3 Author Orcid Image ;   Ryan Aleong3 Author Orcid Image ;   Wendy Tzou3 Author Orcid Image ;   Michael A Rosenberg1, 3 Author Orcid Image
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