Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Study.

Journal: Journal of medical Internet research
PMID: 40373305

Abstract

BACKGROUND: Influenza viruses are major pathogens responsible for acute respiratory infections in humans, which present with symptoms such as fever, cough, sore throat, muscle pain, and fatigue. While molecular diagnostics remain the gold standard, their limited accessibility in resource-poor settings underscores the need for rapid, cost-effective alternatives. Routine blood parameters offer promising predictive value but lack integration into intelligent diagnostic systems for influenza subtyping.

Authors

  • Weiwei Hu
    Department of Osteoporosis and Bone Disease, Shanghai Clinical Research Center of Bone Disease, Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yulong Liu
    Department of Laboratory Medicine, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, 402360, China.
  • Jian Dong
  • Xuelian Peng
    Department of Laboratory Medicine, The Affiliated Dazu's Hospital of Chongqing Medical University, Chongqing, 402360, China.
  • Chunyan Yang
    Research Institute of Extenics and Innovation Method, Guangdong University of Technology, Guangzhou, 510006, China.
  • Honglin Wang
    Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yong Chen
    Department of Urology, Chongqing University Fuling Hospital, Chongqing, China.
  • Shan Shi
    Research Group of Integrated Metallic Nanomaterials Systems, Hamburg University of Technology, Hamburg, Germany; Institute of Materials Mechanics, Helmholtz-Zentrum Hereon, Geesthacht, Germany.
  • Jin Li
    Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.

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