A novel IRBF-RVM model for diagnosis of atrial fibrillation.

Journal: Computer methods and programs in biomedicine
Published Date: May 29, 2019

Abstract

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the common cardiovascular diseases, and electrocardiography (ECG) is a key indicator for the detection and diagnosis of AF and other heart diseases. In this study, an improved machine learning method is proposed for rapid modeling and accurate diagnosis of AF.

Authors

  • Dongdong Kong
    School of Mechatronic Engineering and Automation, Shanghai University, 99 Shanghai Road, Shanghai, China. Electronic address: kodon007@163.com.
  • Junjiang Zhu
    College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou, China. Electronic address: zjj602@yeah.net.
  • Shangshi Wu
    Department of Cardiovascular Medicine, Shanghai Tenth People's Hospital, Shanghai, China. Electronic address: shangshishanghai@163.com.
  • Chaoqun Duan
    School of Mechatronic Engineering and Automation, Shanghai University, 99 Shanghai Road, Shanghai, China. Electronic address: duancq@mie.utoronto.ca.
  • Lixin Lu
    School of Mechatronic Engineering and Automation, Shanghai University, 99 Shanghai Road, Shanghai, China. Electronic address: lulixin@shu.edu.cn.
  • Dongxing Chen
    School of Mechatronic Engineering and Automation, Shanghai University, 99 Shanghai Road, Shanghai, China. Electronic address: cdx617@sina.com.

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