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

Cardiac Arrhythmia, Atrial Fibrillation (141) Decision Support for Health Professionals (2246) Advanced Data Analytics in eHealth (351) Coronary Heart Disease (154) Theme Issue: Bayesian Methods In Medical Research (37) Artificial Intelligence (4806)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59380, first published .
Doctor in lab coat analyzing medical data on computer screen

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;26(3):310 View

Conference Proceedings

  1. Ha D, Schlender T, van der Linden Y, Bosman P, Alderliesten T. Proceedings of the Genetic and Evolutionary Computation Conference Companion. Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data View