Machine Learning Approach to Predict Ventricular Fibrillation Based on QRS Complex Shape

Machine Learning Approach to Predict Ventricular Fibrillation Based on QRS Complex Shape

Early prediction of the occurrence of ventricular tachyarrhythmia (VTA) has a potential to save patients’ lives. VTA includes ventricular tachycardia (VT) and ventricular fibrillation (VF). Several studies have achieved promising performances in predicting VT and VF using traditional heart rate vari...

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Bibliographic Details
Main Authors: Getu Tadele Taye, Eun Bo Shim, Han-Jeong Hwang, Ki Moo Lim
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Physiology
Subjects:
prediction accuracy
QRS complex shape
QRS complex singed area
R-peak amplitude
ventricular fibrillation
ventricular tachyarrhythmia
Online Access:https://www.frontiersin.org/article/10.3389/fphys.2019.01193/full

Internet

https://www.frontiersin.org/article/10.3389/fphys.2019.01193/full

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