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

作     者：Zi-xiao WANG James NTAMBARA Yan LU Wei DAI Rui-jun MENG Dan-min QIAN Zi-xiao WANG;James NTAMBARA;Yan LU;Wei DAI;Rui-jun MENG;Dan-min QIAN

作者机构：Department of Medical InformaticsSchool of MedicineNantong UniversityNantong 226001China Department of Computer ScienceCollege of Engineering and Computing SciencesNew York Institute of TechnologyNew York 10023USA Department of Computer ScienceCollege of Overseas EducationNanjing University of Posts and TelecommunicationsNanjing 210023China Department of EpidemiologySchool of Public HealthNantong UniversityNantong 226019China Artificial Intelligence Laboratory CenterDe Montfort University of LeicesterLeicester LE1 9BHUnited Kingdom 

出 版 物：《Current Medical Science》 (当代医学科学（英文）)

年 卷 期：2022年第42卷第1期

页      面：226-236页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020205[经济学-产业经济学] 

基　　金：This project was supported by grants from the Ministry of Education Humanities and Social Sciences Research Fund Project 

主　　题：influenza prediction data-driven Support Vector Machine Discriminant Analysis Ensemble Classifier 

摘      要：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.