Prediction of all-cause mortality in coronary artery disease patients with atrial fibrillation based on machine learning models.

Journal: BMC cardiovascular disorders
Published Date: Oct 16, 2021

Abstract

BACKGROUND: Machine learning (ML) can include more diverse and more complex variables to construct models. This study aimed to develop models based on ML methods to predict the all-cause mortality in coronary artery disease (CAD) patients with atrial fibrillation (AF).

Authors

  • Xinyun Liu
    Soochow University, Suzhou, 215006, Jiangsu, People's Republic of China.
  • Jicheng Jiang
    Big Data Center for Cardiovascular Disease, Fuwai Central China Cardiovascular Hospital, Zhengzhou, 451450, Henan, People's Republic of China.
  • Lili Wei
    Shandong Institute for Food and Drug Control, Ji'nan 250101, China.
  • Wenlu Xing
    Big Data Center for Cardiovascular Disease, Fuwai Central China Cardiovascular Hospital, Zhengzhou, 451450, Henan, People's Republic of China.
  • Hailong Shang
    Department of Medical Imaging, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028, Jiangsu, People's Republic of China.
  • Guangan Liu
    Department of Cardiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, No. 118 Suzhou Industrial Park Wansheng Street, Suzhou, 215028, Jiangsu, People's Republic of China.
  • Feng Liu
    Department of Vascular and Endovascular Surgery, The First Medical Center of Chinese PLA General Hospital, 100853 Beijing, China.

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