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

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...

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Autores principales: Hu, Hongping, Wang, Haiyan, Wang, Feng, Langley, Daniel, Avram, Adrian, Liu, Maoxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861130/
https://www.ncbi.nlm.nih.gov/pubmed/29559649
http://dx.doi.org/10.1038/s41598-018-23075-1
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author Hu, Hongping
Wang, Haiyan
Wang, Feng
Langley, Daniel
Avram, Adrian
Liu, Maoxing
author_facet Hu, Hongping
Wang, Haiyan
Wang, Feng
Langley, Daniel
Avram, Adrian
Liu, Maoxing
author_sort Hu, Hongping
collection PubMed
description 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.
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spelling pubmed-58611302018-03-26 Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network Hu, Hongping Wang, Haiyan Wang, Feng Langley, Daniel Avram, Adrian Liu, Maoxing Sci Rep Article 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. Nature Publishing Group UK 2018-03-20 /pmc/articles/PMC5861130/ /pubmed/29559649 http://dx.doi.org/10.1038/s41598-018-23075-1 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hu, Hongping
Wang, Haiyan
Wang, Feng
Langley, Daniel
Avram, Adrian
Liu, Maoxing
Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title_full Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title_fullStr Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title_full_unstemmed Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title_short Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
title_sort prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861130/
https://www.ncbi.nlm.nih.gov/pubmed/29559649
http://dx.doi.org/10.1038/s41598-018-23075-1
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