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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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Autori principali: Dodon Turianto Nugrahadi, Rudy Herteno, Dwi Kartini, Muhammad Haekal, Mohammad Reza Faisal
Natura: Artigo
Lingua:Inglês
Pubblicazione: Lublin University of Technology 2023-06-01
Serie:Journal of Computer Sciences Institute
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Accesso online:https://ph.pollub.pl/index.php/jcsi/article/view/3273
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