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Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture

The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature ventricular contraction, atrial premature contrac...

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Dettagli Bibliografici
Pubblicato in:J Healthc Eng
Autori principali: Kim, Jeong-Hwan, Seo, Seung-Yeon, Song, Chul-Gyu, Kim, Kyeong-Seop
Natura: Artigo
Lingua:Inglês
Pubblicazione: Hindawi 2019
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6512052/
https://ncbi.nlm.nih.gov/pubmed/31183029
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2019/2826901
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