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A predictive analytics model for COVID-19 pandemic using artificial neural networks
The COVID-19 pandemic spread rapidly around the world and is currently one of the most leading causes of death and heath disaster in the world. Turkey, like most of the countries, has been negatively affected by COVID-19. The aim of this study is to design a predictive model based on artificial neur...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556691/ http://dx.doi.org/10.1016/j.dajour.2021.100007 |
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author | Kuvvetli, Yusuf Deveci, Muhammet Paksoy, Turan Garg, Harish |
author_facet | Kuvvetli, Yusuf Deveci, Muhammet Paksoy, Turan Garg, Harish |
author_sort | Kuvvetli, Yusuf |
collection | PubMed |
description | The COVID-19 pandemic spread rapidly around the world and is currently one of the most leading causes of death and heath disaster in the world. Turkey, like most of the countries, has been negatively affected by COVID-19. The aim of this study is to design a predictive model based on artificial neural network (ANN) model to predict the future number of daily cases and deaths caused by COVID-19 in a generalized way to fit different countries’ spreads. In this study, we used a dataset between 11 March 2020 and 23 January 2021 for different countries. This study provides an ANN model to assist the government to take preventive action for hospitals and medical facilities. The results show that there is an 86% overall accuracy in predicting the mortality rate and 87% in predicting the number of cases. |
format | Online Article Text |
id | pubmed-8556691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85566912021-11-01 A predictive analytics model for COVID-19 pandemic using artificial neural networks Kuvvetli, Yusuf Deveci, Muhammet Paksoy, Turan Garg, Harish Decision Analytics Journal Article The COVID-19 pandemic spread rapidly around the world and is currently one of the most leading causes of death and heath disaster in the world. Turkey, like most of the countries, has been negatively affected by COVID-19. The aim of this study is to design a predictive model based on artificial neural network (ANN) model to predict the future number of daily cases and deaths caused by COVID-19 in a generalized way to fit different countries’ spreads. In this study, we used a dataset between 11 March 2020 and 23 January 2021 for different countries. This study provides an ANN model to assist the government to take preventive action for hospitals and medical facilities. The results show that there is an 86% overall accuracy in predicting the mortality rate and 87% in predicting the number of cases. The Authors. Published by Elsevier Inc. 2021-11 2021-10-30 /pmc/articles/PMC8556691/ http://dx.doi.org/10.1016/j.dajour.2021.100007 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kuvvetli, Yusuf Deveci, Muhammet Paksoy, Turan Garg, Harish A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title | A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title_full | A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title_fullStr | A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title_full_unstemmed | A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title_short | A predictive analytics model for COVID-19 pandemic using artificial neural networks |
title_sort | predictive analytics model for covid-19 pandemic using artificial neural networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8556691/ http://dx.doi.org/10.1016/j.dajour.2021.100007 |
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