Comparison of shallow and deep learning methods of ECG signals clas-sification for arrhythmia detection

The research aimed to compare the classification performance of arrhythmia classification from the ECG signal dataset from the Massachusetts Institute of Technology–Beth Israel Hospital (MIT-BIH) database. Shallow learning methods that were used in this study are Support Vector Machine, Naïve Baye...

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Bibliographic Details
Published in:	Journal of Computer Sciences Institute
Main Authors:	Dodon Turianto Nugrahadi, Rudy Herteno, Dwi Kartini, Muhammad Haekal, Mohammad Reza Faisal
Format:	Article
Language:	English
Published:	Lublin University of Technology 2023-06-01
Subjects:	ECG signals arrhythmia classification shallow learning deep learning
Online Access:	https://ph.pollub.pl/index.php/jcsi/article/view/3273

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