Multi-label classification of reduced-lead ECGs using an interpretable deep convolutional neural network
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/ac73d5
Abstract: Objective. We propose a model that can perform multi-label classification on 26 cardiac abnormalities from reduced lead Electrocardiograms (ECGs) and interpret the model. Approach. PhysioNet/computing in cardiology (CinC) challenge 2021 datasets are used to train… read more here.
Keywords: reduced lead; lead ecgs; deep convolutional; multi label ... See more keywords
Arrhythmia classification of 12-lead and reduced-lead electrocardiograms via recurrent networks, scattering, and phase harmonic correlation
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DOI: 10.1088/1361-6579/ac77d1
Abstract: We describe an automatic classifier of arrhythmias based on 12-lead and reduced-lead electrocardiograms. Our classifier comprises four modules: scattering transform (ST), phase harmonic correlation (PHC), depthwise separable convolutions (DSC), and a long short-term memory (LSTM)… read more here.
Keywords: reduced lead; lead reduced; lead electrocardiograms; correlation ... See more keywords
The Reconstruction of a 12-Lead Electrocardiogram from a Reduced Lead Set Using a Focus Time-Delay Neural Network.
Sign Up to like & getrecommendations! Published in 2021 at "Acta Cardiologica Sinica"
DOI: 10.6515/acs.202101_37(1).20200712a
Abstract: Background The 12-lead electrocardiogram (ECG) is the gold-standard ECG method used by cardiologists. However, accurate electrode placement is difficult and time consuming, and can lead to incorrect interpretation. Objectives The objective of this study was… read more here.
Keywords: lead electrocardiogram; lead set; reduced lead; time ... See more keywords