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

Cardiac Arrhythmia, Atrial Fibrillation (116) Coronary Heart Disease (113) Advanced Data Analytics in eHealth (225) Decision Support for Health Professionals (1594) Artificial Intelligence (2252) Theme Issue: Bayesian Methods In Medical Research (30)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59380, first published .
Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach

Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach

Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach

Authors of this article:

João Miguel Alves1, 2 Author Orcid Image ;   Daniel Matos3 Author Orcid Image ;   Tiago Martins1, 2 Author Orcid Image ;   Diogo Cavaco3 Author Orcid Image ;   Pedro Carmo3 Author Orcid Image ;   Pedro Galvão3 Author Orcid Image ;   Francisco Moscoso Costa3 Author Orcid Image ;   Francisco Morgado3 Author Orcid Image ;   António Miguel Ferreira3 Author Orcid Image ;   Pedro Freitas3 Author Orcid Image ;   Cláudia Camila Dias1, 2 Author Orcid Image ;   Pedro Pereira Rodrigues1, 2 Author Orcid Image ;   Pedro Adragão3 Author Orcid Image
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Journals

  1. Chatterjee K, Verma A, Godinez E, Gonzalez D, Devathu R, Alhusseini M, Fazal M, Baykaner T. Artificial intelligence in atrial fibrillation – Timely diagnosis, risk assessment and personalized management. Indian Pacing and Electrophysiology Journal 2026 View