Validation of ablation site classification accuracy and trends in the prediction of potential reconnection sites for atrial fibrillation using the CARTONET® R12.1 model

Validation of ablation site classification accuracy and trends in the prediction of potential reconnection sites for atrial fibrillation using the CARTONET® R12.1 model

Abstract Background CARTONET® enables automatic ablation site classification and reconnection site prediction using machine learning. However, the accuracy of the site classification model and trends of the site prediction model for potential reconnection sites are uncertain. Methods We studied a to...

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Bibliographic Details
Main Authors: Wataru Sasaki, Naomichi Tanaka, Kazuhisa Matsumoto, Daisuke Kawano, Masataka Narita, Tsukasa Naganuma, Kenta Tsutsui, Hitoshi Mori, Yoshifumi Ikeda, Takahide Arai, Kazuo Matsumoto, Ritsushi Kato
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Journal of Arrhythmia
Subjects:
automatic classification
CARTONET®
external validation
machine learning
pulmonary vein isolation
Online Access:https://doi.org/10.1002/joa3.13131

Internet

https://doi.org/10.1002/joa3.13131

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