A machine learning-based predictive model for the in-hospital mortality of critically ill patients with atrial fibrillation.

Journal: International journal of medical informatics
Published Date: Jul 31, 2024

Abstract

BACKGROUND: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and significantly raises the in-hospital mortality rate. Existing scoring systems or models have limited predictive capabilities for AF patients in ICU. Our study developed and validated machine learning models to predict the risk of in-hospital mortality in ICU patients with AF.

Authors

  • Yanting Luo
    Department of Cardiovascular Medicine, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Ruimin Dong
    Department of Cardiovascular Medicine, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Jinlai Liu
    Department of Cardiovascular Medicine, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Bingyuan Wu
    Department of Cardiovascular Medicine, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China. Electronic address: wubingy3@mail.sysu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals