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

Rachel S Kim   1 , BA ;   Steven Simon   2 , MD ;   Brett Powers   1 , MSc ;   Amneet Sandhu   3 , MD ;   Jose Sanchez   3 , MD ;   Ryan T Borne   3 , MD ;   Alexis Tumolo   3 , MD ;   Matthew Zipse   3 , MD ;   J Jason West   3 , MD ;   Ryan Aleong   3 , MD ;   Wendy Tzou   3 , MD ;   Michael A Rosenberg   1, 3 , MD

1 Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, United States

2 Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States

3 Clinical Cardiac Electrophysiology Section, Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States

Corresponding Author:

  • Michael A Rosenberg, MD
  • Clinical Cardiac Electrophysiology Section
  • Division of Cardiology
  • University of Colorado School of Medicine
  • 12631 East 17th Avenue
  • Mail Stop B130
  • Aurora, CO, 80045
  • United States
  • Phone: 1 (303) 724 8391
  • Email: michael.a.rosenberg@cuanschutz.edu