Machine learning for the prediction of acute kidney injury and paraplegia after thoracoabdominal aortic aneurysm repair.

Journal: Journal of cardiac surgery
Published Date: Jan 1, 2020

Abstract

OBJECTIVE: Prediction of acute renal failure (ARF) and paraplegia after thoracoabdominal aortic aneurysm repair (TAAAR) is helpful for decision-making during the postoperative phase. To find a more efficient method for making a prediction, we performed tests on the efficacy of different machine learning predicting models.

Authors

  • Chenyang Zhou
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
  • Rong Wang
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shanxi, China. Electronic address: wangrong91@nwsuaf.edu.cn.
  • Wenjian Jiang
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
  • Junming Zhu
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
  • Yongmin Liu
    Key Laboratory of Biorheology Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400044, China.
  • Jun Zheng
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
  • Xiaolong Wang
    Cardiovascular Department, Shuguang Hospital Affiliated to Shanghai University of TCM Shanghai, China.
  • Wei Shang
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
  • Lizhong Sun
    Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

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