ECG Morphological Decomposition for Automatic Rhythm Identification

Abstract
Manual rhythm classification in 12-lead ECGs is time-consuming and operator-biased. We present an automatic ECG classifier using CinC's 2020 challenge dataset. In the first phase of the Challenge, 9 categories were targeted with an ensemble of 4 classifiers. In the second phase, 7 classifiers were implemented to detect 24 cardiac electrophysiological disorders. Five classifiers identified abnormalities in different specific regions of the...
Paper Details
Title
ECG Morphological Decomposition for Automatic Rhythm Identification
Published Date
Dec 30, 2020
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