Patient-specific ECG classification based on recurrent neural networks and clustering technique

In this paper, we propose a novel patient-specific electrocardiogram (ECG) classification algorithm based on the recurrent neural networks (RNN) and density based clustering technique. We use RNN to learn time correlation among ECG signal points and to classify ECG beats with different heart rates....

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Vydané v:	2017 13th IASTED International Conference on Biomedical Engineering (BioMed) s. 63 - 67
Hlavní autori:	Zhang, Chenshuang, Wang, Guijin, Zhao, Jingwei, Gao, Pengfei, Lin, Jianping, Yang, Huazhong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	International Association of Science and Technology for Development--IASTED 2017
Predmet:	Classification algorithms Data models Deep Learning Density Based Clustering Algorithm Diseases ECG Classification Electrocardiography Morphology Recurrent neural networks Transforms
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