An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.

Journal: BMC anesthesiology
PMID: 39702008

Abstract

AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) transfusion during hip fracture surgery.

Authors

  • Yongchang Zhou
    Department of Anesthesiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510030, Guangdong, China.
  • Suo Wang
    Guangzhou University of Chinese Medicine, Guangzhou, 510030, Guangdong, China.
  • Zhikun Wu
    Department of Anesthesiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510030, Guangdong, China.
  • Weixing Chen
    Department of Data Science, Guangzhou AID Cloud Technology, Guangzhou, 510663, China.
  • Dong Yang
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology Xi'an 710021 China yangdong@sust.edu.cn.
  • Chaojin Chen
    Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 10630, Guangdong, People's Republic of China.
  • Gaofeng Zhao
    Department of Anesthesiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510030, Guangdong, China.
  • Qingxiong Hong
    Department of Anesthesiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510030, Guangdong, China. hongqingxiong@gzucm.edu.cn.

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