Machine learning based early mortality prediction in the emergency department.

Journal: International journal of medical informatics
Published Date: Sep 8, 2021

Abstract

BACKGROUND: It is a great challenge for emergency physicians to early detect the patient's deterioration and prevent unexpected death through a large amount of clinical data, which requires sufficient experience and keen insight.

Authors

  • Cong Li
    Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science, National Demonstration Center for Experimental Chemistry Education, Northwest University, Xi'an, Shaanxi 710127, China. Electronic address: licong@nwu.edu.cn.
  • Zhuo Zhang
  • Yazhou Ren
    SMILE Lab, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Hu Nie
    Emergency Department, West China Hospital, Sichuan University, Chengdu, China. Electronic address: dr.hu.nie@gmail.com.
  • Yuqing Lei
    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Hang Qiu
    School of Computer Science and Engineering, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, Sichuan, P.R. China. qiuhang@uestc.edu.cn.
  • Zenglin Xu
    Big Data Research Center, University of Electronic Science & Technology, Chengdu, Sichuan, China; School of Computer Science and Engineering, University of Electronic Science & Technology, Chengdu, Sichuan, China. Electronic address: zlxu@uestc.edu.cn.
  • Xiaorong Pu
    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R.China;Health Big Data Institute of Big Data Center, University of Electronic Science and Technology of China, Chengdu 611731, P.R.China.

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