Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network

This study proposed an efficient ECG preprocessing technique, and the preprocessed ECG data was subsequently used to classify atrial fibrillation (AFib) using end-to-end deep neural networks. This is significant since early identification of AFib can help to prevent mortality. With this in mind, the...

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Bibliographic Details

Published in:	Expert systems with applications Vol. 233; p. 120975
Main Authors:	Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.12.2023
Subjects:	Atrial fibrillation Convolutional neural network Denoising autoencoders Electrocardiography Long short-term memory Electrocardiography Long short-term memory Denoising autoencoders Atrial fibrillation Convolutional neural network
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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