[A DenseNet-based diagnosis algorithm for automated diagnosis using clinical ECG data].

Journal: Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Published Date: Jan 30, 2019

Abstract

OBJECTIVE: To train convolutional networks using multi-lead ECG data and classify new data accurately to provide reliable information for clinical diagnosis.

Authors

  • Jiewei Lai
    School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
  • Yundai Chen
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Baoshi Han
    Department of Cardiology, Chinese PLA General Hospital, Beijing 100853, China.
  • Lei Ji
    IT department of Chinese, PLA General Hospital, Beijing, China.
  • Yajun Shi
    Department of Cardiology, Chinese PLA General Hospital, Beijing 100853, China.
  • Zhicong Huang
    Cardiocloud Medical Technology (Beijing) Co., Ltd., Beijing 100094, China.
  • Wei Yang
    Key Laboratory of Structure-Based Drug Design and Discovery (Shenyang Pharmaceutical University), Ministry of Education, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016, PR China. Electronic address: 421063202@qq.com.
  • Qianjin Feng
    Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China. Electronic address: qianjinfeng08@gmail.com.

Keywords

External Resources

Popular Topics
Recent Journals