The present work investigates arrhythmias which can be detected from Electrocardiography (ECG) waves. Detecting cardiac arrhythmia helps indeed to prevent sudden and untimely deaths. Here, directional depth-based classifiers are employed to predict the presence or absence of cardiac arrhythmia. A comparison of their performance with respect to the directional Bayes rule is also provided.
Directional supervised learning through depth functions: an application to ECG waves analysis
Houyem Demni
2021-01-01
Abstract
The present work investigates arrhythmias which can be detected from Electrocardiography (ECG) waves. Detecting cardiac arrhythmia helps indeed to prevent sudden and untimely deaths. Here, directional depth-based classifiers are employed to predict the presence or absence of cardiac arrhythmia. A comparison of their performance with respect to the directional Bayes rule is also provided.File in questo prodotto:
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