Predicting Postoperative Circulatory Complications in Older Patients: A Machine Learning Approach.

Journal: Biomedical and environmental sciences : BES
PMID: 40237268

Abstract

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients.

Authors

  • Xiao Yun Hu
    Department of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
  • Wei Xuan Sheng
    Department of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
  • Kang Yu
    Precision Agriculture Lab, School of Life Sciences, Technical University of Munich, Freising, Germany.
  • Jie Tai Duo
    Department of Anesthesiology, Xizang Fukang Cancer Hospital, Lhasa 850000, Xizang, China.
  • Peng Fei Liu
    Department of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
  • Ya Wei Li
    Department of Anesthesiology, Peking University First Hospital, Beijing 100034, China.
  • Dong Xin Wang
    Department of Anesthesiology, Peking University First Hospital, Beijing 100034, China.
  • Hui Hui Miao
    Department of Anesthesiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.

Keywords

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