Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong.

Journal: Current medical science
PMID: 34985610

Abstract

OBJECTIVE: The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and considering the seasonal influenza in Hong Kong, the study aims to establish a Combinatorial Judgment Classifier (CJC) model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning.

Authors

  • Zi-Xiao Wang
    Department of Medical Informatics, School of Medicine, Nantong University, Nantong, 226001, China.
  • James Ntambara
    Department of Epidemiology, School of Public Health, Nantong University, Nantong, 226019, China.
  • Yan Lu
    National Institute of Standards and Technology.
  • Wei Dai
    Department of Intensive Care Unit, The First Affiliated Hospital of Jiangxi Medical College, Shangrao, Jiangxi, China.
  • Rui-Jun Meng
    Department of Medical Informatics, School of Medicine, Nantong University, Nantong, 226001, China.
  • Dan-Min Qian
    Department of Medical Informatics, School of Medicine, Nantong University, Nantong, 226001, China. qdm11@163.com.

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