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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Veröffentlicht in:	Expert systems with applications Jg. 233; S. 120975
Hauptverfasser:	Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.12.2023
Schlagworte:	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-Zugang:	Volltext
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