Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.

Journal: Annals of medicine
PMID: 39155811

Abstract

BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm.

Authors

  • Yongbin Wang
    Department of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P.R. China.
  • Xu Sun
    MOE Key Laboratory of Computational Linguistics, School of EECS, Peking University, Beijing, China; Center for Data Science, Peking University, Beijing, China. Electronic address: xusun@pku.edu.cn.
  • Jianhong Lu
    Department of Intensive Care Unit, Huzhou Central Hospital, Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, China.
  • Lei Zhong
    Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Zhenzhen Yang
    Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, China.

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