Extensive deep learning model to enhance electrocardiogram application via latent cardiovascular feature extraction from identity identification.

Journal: Computer methods and programs in biomedicine
PMID: 36738606

Abstract

BACKGROUND AND OBJECTIVE: Deep learning models (DLMs) have been successfully applied in biomedicine primarily using supervised learning with large, annotated databases. However, scarce training resources limit the potential of DLMs for electrocardiogram (ECG) analysis.

Authors

  • Yu-Sheng Lou
    School of Public Health, National Defense Medical Center, Taipei, Taiwan.
  • Chin-Sheng Lin
    Division of Cardiology, Department of Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan.
  • Wen-Hui Fang
    Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan.
  • Chia-Cheng Lee
    Planning and Management Office, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
  • Chin Lin
    School of Public Health, National Defense Medical Center, Taipei, Taiwan.

Keywords

External Resources

Popular Topics
Recent Journals