Mortality predicting models for patients with infective endocarditis: a machine learning approach.

Journal: BMC medical informatics and decision making
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Infective endocarditis (IE) is a fatal cardiovascular disease with varied clinical manifestations but rapid progression. A series of existing risk models helped identify IE patients with high risk, but the imperfect predictive performance and limited application called for better predictive systems.

Authors

  • Yang Zi-Yang
    Department of Geriatric Cardiovascular, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
  • Wang Qi
    Department of Cardiology, Fuwai Hospital, National Clinical Research Center for Cardiovascular Diseases, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Xingyan Liu
    NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
  • Haolin Li
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030024, China.
  • Shouhong Wang
    Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China.
  • Danqing Yu
    Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. gdydq100@126.com.
  • Xuebiao Wei
    Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510100, China. weixuebiao@163.com.

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