Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network

Hongping Hu, Haiyan Wang, Feng Wang, Daniel Langley, Adrian Avram, Maoxing Liu

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may help save lives. In this paper, we use the Twitter data set and the United States Centers for Disease Control's influenza-like illness (ILI) data set to predict a nearly real-time regional unweighted percentage ILI in the United States by use of an artificial neural network optimized by the improved artificial tree algorithm. The results show that the proposed method is an efficient approach to real-time prediction.

Original languageEnglish (US)
Article number4895
JournalScientific reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018

ASJC Scopus subject areas

  • General

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