Machine learning prediction models for stroke-associated pneumonia:Meta-analysis.

Journal: Computers in biology and medicine
Published Date: Jun 25, 2025

Abstract

OBJECTIVE: The heterogeneity of machine learning (ML) models predicting the risk of stroke-associated pneumonia (SAP) is considerable. This study aims to conduct a meta-analysis and comparison of published ML models that predict SAP risk.

Authors

  • Yi Cao
    Department of Dermatology, First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
  • Xi Zeng
  • Yangyang Gou
    School of Nursing, Guizhou Medical University, China. Electronic address: 17835260616@163.com.
  • Yu Lu
    Faw-volkswagen Automative Co., Changchun, China.
  • Dian Zhu
    Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, China. Electronic address: 13612239538@163.com.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Yan Dai
    Laboratory of Veterinary Drug Development and Evaluation, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Liu Jian
    Guangxi Institute of Special Equipment Inspection and Research, Guilin Guangxi, Guilin, China.
  • Peng Min
    Department of Nursing Quality Management, The Affiliated Hospital of Guizhou Medical University, China. Electronic address: Pm1616@163.com.

Keywords

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