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

Cardiac Arrhythmia, Atrial Fibrillation (146) Public Health Informatics (586) Machine Learning (3353) Novel Sensors and Data Acquisition Methods in Cardiology (271) Artificial Intelligence (5055)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77380, first published .
Nurse shows elderly patient a tablet with a heart diagram in a clinic

Predicting Atrial Fibrillation Ablation Outcomes: Machine Learning Model Development and Validation Using a Large Administrative Claims Database

Predicting Atrial Fibrillation Ablation Outcomes: Machine Learning Model Development and Validation Using a Large Administrative Claims Database

Authors of this article:

Yijun Liu1 Author Orcid Image ;   Mustapha Oloko-Oba2 Author Orcid Image ;   Kathryn A Wood2 Author Orcid Image ;   Michael S Lloyd3 Author Orcid Image ;   Joyce C Ho4 Author Orcid Image ;   Vicki Stover Hertzberg2 Author Orcid Image
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Journals

  1. Koh T, Jeong S, Dababneh E, Lal V, Hughes I, Nayyar S. Machine-learning versus traditional scoring methods for prediction of atrial fibrillation recurrence after catheter ablation: A systematic review and meta-analysis. Current Problems in Cardiology 2027;52(1):103484 View