Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

Journal: The Pediatric infectious disease journal
PMID: 38717173

Abstract

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sepsis in the pediatric intensive care unit (PICU).

Authors

  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Yu-Hui Wu
    Department of Ultrasound, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
  • Yong Ren
    Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
  • Fan-Fan Sun
    From the Pediatric Intensive Care Unit, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China.
  • Shao-Hua Tao
    Pediatric Intensive Care Unit, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
  • Hong-Xin Lin
    From the Pediatric Intensive Care Unit, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China.
  • Chuang-Sen Zhang
    From the Pediatric Intensive Care Unit, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China.
  • Wen Tang
    Infervision, Beijing, China.
  • Zhuang-Gui Chen
    Pediatric Intensive Care Unit, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Chun Chen
  • Li-Dan Zhang
    From the Pediatric Intensive Care Unit, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China.

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