ECG classification based on guided attention mechanism.

Journal: Computer methods and programs in biomedicine
Published Date: Oct 3, 2024

Abstract

BACKGROUND AND OBJECTIVE: Integrating domain knowledge into deep learning models can improve their effectiveness and increase explainability. This study aims to enhance the classification performance of electrocardiograms (ECGs) by customizing specific guided mechanisms based on the characteristics of different cardiac abnormalities.

Authors

  • Yangcheng Huang
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
  • Wenjing Liu
    Children Rehabilitation Center, the Affiliated Hospital of Jining Medical University, Jining, China.
  • Ziyi Yin
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Shuaicong Hu
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
  • Mingjie Wang
    Shanghai Key Laboratory of Bioactive Small Molecules, School of Basic Medical Science, Fudan University, Shanghai, 200032, People's Republic of China.
  • Wenjie Cai
    University of Shanghai for Science and Technology, Shanghai, China.

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