An Automated Cardiac Arrhythmia Classification Network for 45 Arrhythmia Classes Using 12-Lead Electrocardiogram

An Automated Cardiac Arrhythmia Classification Network for 45 Arrhythmia Classes Using 12-Lead Electrocardiogram

Electrocardiogram is a non-invasive, inexpensive, and widely used diagnostic tool for arrhythmia diagnosis in clinics. Deep learning techniques have shown great promise in electrocardiogram signal analysis, enabling automatic and accurate detection of various cardiac arrhythmia. This paper proposes...

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Bibliographic Details
Main Authors: Ho Keun Kim, Myung Hoon Sunwoo
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
12-lead electrocardiogram
deep learning
convolutional neural network
multi-label classification
cardiac arrhythmia classification
Online Access:https://ieeexplore.ieee.org/document/10478009/

Internet

https://ieeexplore.ieee.org/document/10478009/

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