[Predicting Intensive Care Unit Mortality in Patients With Heart Failure Combined With Acute Kidney Injury Using an Interpretable Machine Learning Model: A Retrospective Cohort Study].

Journal: Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
PMID: 40109460

Abstract

OBJECTIVE: Heart failure (HF) complicated by acute kidney injury (AKI) significantly impacts patient outcomes, and it is crucial to make early predictions of short-term mortality. This study is focused on developing an interpretable machine learning model to enhance early prediction accuracy in such clinical scenarios.

Authors

  • Xinyao Luo
    （ 610041） Department of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Dingyuan Wan
    （ 610041） Department of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Ke Wang
    China Electric Power Research Institute, Haidian District, Beijing 100192, China. wangke1@epri.sgcc.com.cn.
  • Yupei Li
    （ 610041） Department of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Ruoxi Liao
    （ 610041） Department of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Baihai Su
    （ 610041） Department of Nephrology, Kidney Research Institute, West China Hospital, Sichuan University, Chengdu 610041, China.

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