ECG-surv: A deep learning-based model to predict time to 1-year mortality from 12-lead electrocardiogram.

Journal: Biomedical journal
Published Date: May 1, 2024

Abstract

BACKGROUND: Electrocardiogram (ECG) abnormalities have demonstrated potential as prognostic indicators of patient survival. However, the traditional statistical approach is constrained by structured data input, limiting its ability to fully leverage the predictive value of ECG data in prognostic modeling.

Authors

  • Ching-Heng Lin
    Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
  • Zhi-Yong Liu
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital Linkou Main Branch, Taoyuan, Taiwan.
  • Jung-Sheng Chen
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
  • Yang C Fann
    Bioinformatics Section, National Institute of Neurological Disorder and Stroke, National Institutes of Health, Bethesda, MD, United States. Electronic address: fann@ninds.nih.gov.
  • Ming-Shien Wen
    Division of Cardiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan.
  • Chang-Fu Kuo
    Department of Rheumatology, Allergy, and Immunology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC.

Keywords

External Resources

Popular Topics
Recent Journals