Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs

Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs

Background. Twelve lead ECGs are a core diagnostic tool for cardiovascular diseases. Here, we describe and analyse an ensemble deep neural network architecture to classify 24 cardiac abnormalities from 12 lead ECGs.Method. We proposed a squeeze and excite ResNet to automatically learn deep features...

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Bibliographic Details
Main Authors: Darlington, A. (Author), Fang, H. (Author), Gifford, H. (Author), Murphy, D. (Author), Relton, S.D (Author), Williams, S. (Author), Wong, D.C (Author), Zhao, Z. (Author)
Format: Article
Language:English
Published: NLM (Medline) 2022
Subjects:
Arrhythmias, Cardiac
cardiovascular disease
Cardiovascular Diseases
deep neural network
ECG
electrocardiogram
electrocardiography
Electrocardiography
heart arrhythmia
heart disease
Heart Diseases
human
Humans
machine learning
Neural Networks, Computer
PhysioNet
procedures
signal processing
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Internet

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