CAT-Net: Convolution, attention, and transformer based network for single-lead ECG arrhythmia classification

CAT-Net: Convolution, attention, and transformer based network for single-lead ECG arrhythmia classification

<p>Machine learning technologies have been applied extensively in the last decade to automatically detect and analyze various forms of arrhythmia from electrocardiogram (ECG) signals. Existing deep learning-based models focus on enhancing classification performance by exploring spatial–tempora...

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Bibliographic Details
Main Author: Md Rabiul Islam (6424796) (author)
Other Authors: Marwa Qaraqe (10135172) (author), Khalid Qaraqe (16896504) (author), Erchin Serpedin (3706543) (author)
Published: 2024
Subjects:
Biological sciences
Bioinformatics and computational biology
Biomedical and clinical sciences
Cardiovascular medicine and haematology
Engineering
Biomedical engineering
Information and computing sciences
Machine learning
ECG
CNN
Transformer
Arrhythmia
Attention
Deep learning
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