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 featur...

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Bibliographic Details
Main Authors: Zhibin Zhao, Darcy Murphy, Hugh Gifford, Stefan Williams, Annie Darlington, Samuel Relton, Hui Fang, David C Wong
Format: Default Article
Published: 2022
Subjects:
ECG
deep neural network
machine learning
electrocardiogram
signal processing
PhysioNet
Online Access:https://hdl.handle.net/2134/19337798.v1
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https://hdl.handle.net/2134/19337798.v1

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