Machine Learning Approaches-Driven for Mortality Prediction for Patients Undergoing Craniotomy in ICU.

Journal: Brain injury
PMID: 35080996

Abstract

OBJECTIVES: We aimed to predict the mortality of patients with craniotomy in ICU by using predictive models to extract the high-risk factors leading to the death of patients from a retrospective a study.

Authors

  • Ronguo Yu
    Surgical Intensive Care Unit, Fujian Provincial Hospital, Fujian, China.
  • Shaobo Wang
    College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China.
  • Jingqing Xu
    Surgical Intensive Care Unit, Fujian Provincial Hospital, Fujian, China.
  • Qiqi Wang
    Yidu Cloud (Beijing) Technology Co. Ltd, Beijing, China.
  • Xinjun He
    Yidu Cloud (Beijing) Technology Co. Ltd, Beijing, China.
  • Jun Li
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.
  • Xiuling Shang
    Department of Critical Care Medicine, Fujian Provincial Key Laboratory of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Provincial Center for Critical Care Medicine, Fuzhou, Fujian, China.
  • Han Chen
    School of Statistics, University of Minnesota at Twin Cities.
  • Youjun Liu
    College of Life Science and Bio-Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China. Electronic address: lyjlma@bjut.edu.cn.

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