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

Digital Health Reviews (1807) Artificial Intelligence (2315) Clinical Information and Decision Making (2051) mHealth in a Clinical Setting (768) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1800) Decision Support for Health Professionals (1624) Machine Learning (2212) Cardiac Arrhythmia, Atrial Fibrillation (116) Cardiac Disease Management (166) Clinical Informatics (1421)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60888, first published .
Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review

Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review

Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review

Authors of this article:

Aijing Luo1, 2, 3, 4 Author Orcid Image ;   Wei Chen1, 2, 3, 4 Author Orcid Image ;   Hongtao Zhu1, 3, 4, 5 Author Orcid Image ;   Wenzhao Xie2, 3, 4, 6 Author Orcid Image ;   Xi Chen1, 4, 5 Author Orcid Image ;   Zhenjiang Liu1, 4, 7 Author Orcid Image ;   Zirui Xin1, 3, 4, 5 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Marascu G, Deaconu A, Mitran R, Stanciulescu L, Vatasescu R. Targeting the Substrate: Mechanism-Based Ablation Strategies for Persistent Atrial Fibrillation. Journal of Clinical Medicine 2025;14(14):5147 View
  2. Zhou L, Zhao Y, Song W, Li Y, Wang J, Gong H, Sun G, Bao Z. Explainable machine learning for risk prediction of acute cardiac tamponade during atrial fibrillation ablation. Scientific Reports 2026 View

Books/Policy Documents

  1. Zlatar A, Divers A. Oxford Intersections: AI in Society. View

Conference Proceedings

  1. Wang X, Wang H, Fu R. Proceedings of the 2025 International Conference on Health Informatization and Data Analytics. Boosting Cardiovascular Disease Prediction Accuracy: A Hybrid AI Strategy Integrating LLM-Generated Risk Scores View