Predictive Power for Thrombus Detection after Atrial Appendage Closure: Machine Learning vs. Classical Methods

Predictive Power for Thrombus Detection after Atrial Appendage Closure: Machine Learning vs. Classical Methods

Device-related thrombus (DRT) after left atrial appendage (LAA) closure is infrequent but correlates with an increased risk of thromboembolism. Therefore, the search for DRT predictors is a topic of interest. In the literature, multivariable methods have been used achieving non-consistent results, a...

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Bibliographic Details
Main Authors: Pablo Antúnez-Muiños, Víctor Vicente-Palacios, Pablo Pérez-Sánchez, Jesús Sampedro-Gómez, Antonio Sánchez-Puente, Pedro Ignacio Dorado-Díaz, Luis Nombela-Franco, Pablo Salinas, Hipólito Gutiérrez-García, Ignacio Amat-Santos, Vicente Peral, Antonio Morcuende, Lluis Asmarats, Xavier Freixa, Ander Regueiro, Berenice Caneiro-Queija, Rodrigo Estevez-Loureiro, Josep Rodés-Cabau, Pedro Luis Sánchez, Ignacio Cruz-González
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Journal of Personalized Medicine
Subjects:
left atrial appendage closure
device-related thrombosis
atrial fibrillation
machine learning
multivariable analysis
predictors
Online Access:https://www.mdpi.com/2075-4426/12/9/1413

Internet

https://www.mdpi.com/2075-4426/12/9/1413

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