Incorporating Latent Variables Using Nonnegative Matrix Factorization Improves Risk Stratification in Brugada Syndrome

Incorporating Latent Variables Using Nonnegative Matrix Factorization Improves Risk Stratification in Brugada Syndrome

Background A combination of clinical and electrocardiographic risk factors is used for risk stratification in Brugada syndrome. In this study, we tested the hypothesis that the incorporation of latent variables between variables using nonnegative matrix factorization can improve risk stratification...

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Bibliographic Details
Main Authors: Gary Tse, Jiandong Zhou, Sharen Lee, Tong Liu, George Bazoukis, Panagiotis Mililis, Ian C. K. Wong, Cheng Chen, Yunlong Xia, Tsukasa Kamakura, Takeshi Aiba, Kengo Kusano, Qingpeng Zhang, Konstantinos P. Letsas
Format: Article
Language:English
Published: Wiley 2020-11-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
Brugada syndrome
depolarization
ECG
latent variable
nonnegative matrix factorization
repolarization
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.119.012714

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.119.012714

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