Generalization of Convolutional Neural Networks for ECG Classification Using Generative Adversarial Networks

Generalization of Convolutional Neural Networks for ECG Classification Using Generative Adversarial Networks

Electrocardiograms (ECGs) play a vital role in the clinical diagnosis of heart diseases. An ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our work is based on 15 different classes from the MIT-BIH arrhythmia dataset. But the MIT-BIH dataset is strongly imbala...

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Bibliographic Details
Main Authors: Abdelrahman M. Shaker, Manal Tantawi, Howida A. Shedeed, Mohamed F. Tolba
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Class imbalance
convolution neural networks (CNNs)
ECG classification
generative adversarial networks (GANs)
Online Access:https://ieeexplore.ieee.org/document/9000871/

Internet

https://ieeexplore.ieee.org/document/9000871/

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