Multi-label classification of arrhythmia using dynamic graph convolutional network based on encoder-decoder framework-Reference-Cited by-同舟云学术

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Multi-label classification of arrhythmia using dynamic graph convolutional network based on encoder-decoder framework

Published:2024-09 Issue: Volume:95 Page:106348
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Cheng Yuhao,Zhu Wenliang,Li Deyin,Wang Lirong^ORCID

Publisher

Elsevier BV

Reference35 articles.

1. Global public health problem of sudden cardiac death;Mehra;J. Electrocardiol.,2007

2. A new approach to detection of ECG arrhythmias: complex discrete wavelet transform based complex valued artificial neural network;Özbay;J. Med. Syst.,2009

3. A comparative study of DWT, CWT and DCT transformations in ECG arrhythmias classification;Khorrami;Expert Syst. Appl.,2010

4. Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models;Seera;Expert Syst. Appl.,2015

5. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals;Elhaj;Comput. Methods Programs Biomed.,2016

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