Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data

Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data

The treatment of outflow tract ventricular arrhythmias (OTVA) through radiofrequency ablation requires the precise identification of the site of origin (SOO). Pinpointing the SOO enhances the likelihood of a successful procedure, reducing intervention times and recurrence rates. Current clinical met...

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Bibliographic Details
Main Authors: Álvaro J. Bocanegra-Pérez, Gemma Piella, Rafael Sebastian, Guillermo Jimenez-Perez, Giulio Falasconi, Andrea Saglietto, David Soto-Iglesias, Antonio Berruezo, Diego Penela, Oscar Camara
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-03-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
electrocardiogram
feature analysis
machine learning
outflow tract ventricular arrhythmias
site of origin
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2024.1353096/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2024.1353096/full

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