Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms.

Journal: BMC medical research methodology
PMID: 37259031

Abstract

OBJECTIVE: PONV reduces patient satisfaction and increases hospital costs as patients remain in the hospital for longer durations. In this study, we build a preliminary artificial intelligence algorithm model to predict early PONV in patients.

Authors

  • Cheng-Mao Zhou
    Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Henan, China. zhouchengmao187@foxmail.com.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Qiong Xue
    Department of Anesthesiology, Pain, and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • Jian-Jun Yang
    School of Medicine, Southeast University, Nanjing, China.
  • Yu Zhu
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, Jiangsu, China.

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