Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. Howev...

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Bibliografiske detaljer
Udgivet i:	Front Physiol
Main Authors:	Sánchez, Jorge, Luongo, Giorgio, Nothstein, Mark, Unger, Laura A., Saiz, Javier, Trenor, Beatriz, Luik, Armin, Dössel, Olaf, Loewe, Axel
Format:	Artigo
Sprog:	Inglês
Udgivet:	Frontiers Media S.A. 2021
Fag:	Physiology
Online adgang:	https://ncbi.nlm.nih.gov/pmc/articles/PMC8287829/ https://ncbi.nlm.nih.gov/pubmed/34290623 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fphys.2021.699291
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Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

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