Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images

Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images

Abstract Background As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the condition has become the epicenter of a plethora of ECG diagnostic research. In recent diagnostic methodologies, Morse Continuous Wavelet Transform (MsCWT) is a feature extraction technique uti...

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Bibliographic Details
Main Authors: Ling-Chun Sun, Chia-Chiang Lee, Hung-Yen Ke, Chih-Yuan Wei, Ke-Feng Lin, Shih-Sung Lin, Hsin Hsiu, Ping-Nan Chen
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Atrial fibrillation
MsCWT
Convolutional Neural Network
ResNet101
Online Access:https://doi.org/10.1186/s12911-025-02872-5
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