Why the study?
Predicting the occurrence of ventricular tachyarrhythmia in advance is critical for saving the lives of cardiac arrhythmia patients.
Does a 1-D CNN improve the prediction accuracy of ventricular tachyarrhythmia onset compared to traditional machine learning algorithms?
Comparison
1-D CNN vs ANN, SVM, and KNN using 11 HRV features
Authors
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May aid imminent VTA risk stratification via HRV; leaves open prospective validation before clinical use.
Does a 1-D CNN improve the prediction accuracy of ventricular tachyarrhythmia onset compared to traditional machine learning algorithms?
A 1-D CNN using HRV features provides higher accuracy for predicting imminent ventricular tachyarrhythmia compared to traditional machine learning algorithms.
Taye et al. (2020) studied this question.
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