Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PMID: 38657830

Abstract

BACKGROUND: Acute kidney injury (AKI) is not only a complication but also a serious threat to patients with cerebral infarction (CI). This study aimed to explore the application of interpretable machine learning algorithms in predicting AKI in patients with cerebral infarction.

Authors

  • Xiaochi Lu
    Department of Emergency medicine, Lishui Municipal Central Hospital, Lishui, 323000, PR China.
  • Yi Chen
    Department of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Gongping Zhang
    Department of Emergency medicine, Lishui Municipal Central Hospital, Lishui, 323000, PR China.
  • Xu Zeng
  • Linjie Lai
    Department of Emergency medicine, Lishui Municipal Central Hospital, Lishui, 323000, PR China.
  • Chaojun Qu
    Department of Intensive care unit, Lishui Municipal Central Hospital, Lishui, 323000, PR China. Electronic address: quchaojun6496@163.com.

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