Development, External Validation, and Visualization of Machine Learning Models for Predicting Occurrence of Acute Kidney Injury after Cardiac Surgery.

Journal: Reviews in cardiovascular medicine
Published Date: Aug 9, 2023

Abstract

BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in short- and long-term mortality among patients. Here, we adopted machine learning algorithms to build prediction models with the overarching goal of identifying patients who are at a high risk of such unfavorable kidney outcomes.

Authors

  • Jiakang Shao
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Feng Liu
    Department of Vascular and Endovascular Surgery, The First Medical Center of Chinese PLA General Hospital, 100853 Beijing, China.
  • Shuaifei Ji
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Chao Song
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Yan Ma
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Ming Shen
    Department of Cardiovascular Medicine, The First Hospital of Hebei Medical University, 050000 Shijiazhuang, Hebei, China.
  • Yuntian Sun
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Siming Zhu
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Yilong Guo
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Bing Liu
    Department of Cardiovascular Surgery, the Sixth Medical Centre of Chinese PLA General Hospital, 100048 Beijing, China.
  • Yuanbin Wu
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Handai Qin
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Shengwei Lai
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Yunlong Fan
    Medical School of Chinese PLA, 100853 Beijing, China.

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