Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.
Journal:
Circulation. Arrhythmia and electrophysiology
PMID:
32536204
Abstract
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a methodology that combines machine learning (ML) and personalized computational modeling to predict, before PVI, which patients are most likely to experience AF recurrence after PVI.
Authors
Keywords
Action Potentials
Aged
Atrial Fibrillation
Catheter Ablation
Contrast Media
Diagnosis, Computer-Assisted
Female
Heart Rate
Humans
Machine Learning
Magnetic Resonance Imaging
Male
Meglumine
Middle Aged
Models, Cardiovascular
Organometallic Compounds
Patient-Specific Modeling
Predictive Value of Tests
Proof of Concept Study
Pulmonary Veins
Recurrence
Reproducibility of Results
Retrospective Studies
Risk Assessment
Risk Factors
Treatment Outcome