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Data Mining Based Techniques for Covid-19 Predictions
COVID-19 is a pandemic that has resulted in numerous fatalities and infections in recent years, with a rising tendency in both the number of infections and deaths and the pace of recovery. Accurate forecasting models are important for making accurate forecasts and taking relevant actions. As a resul...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886325/ https://www.ncbi.nlm.nih.gov/pubmed/36743794 http://dx.doi.org/10.1016/j.procs.2023.01.003 |
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author | Rane, Rahul Dubey, Aditya Rasool, Akhtar Wadhvani, Rajesh |
author_facet | Rane, Rahul Dubey, Aditya Rasool, Akhtar Wadhvani, Rajesh |
author_sort | Rane, Rahul |
collection | PubMed |
description | COVID-19 is a pandemic that has resulted in numerous fatalities and infections in recent years, with a rising tendency in both the number of infections and deaths and the pace of recovery. Accurate forecasting models are important for making accurate forecasts and taking relevant actions. As a result, accurate short-term forecasting of the number of new cases that are contaminated and recovered is essential for making the best use of the resources at hand and stopping or delaying the spread of such illnesses. This paper shows the various techniques for forecasting the covid-19 cases. This paper classifies the various models according to their category and shows the merits and demerits of various fore-casting techniques. The research provides insight into potential issues that may arise during the forecasting of covid-19 instances for predicting the positive, negative, and death cases in this pandemic. In this paper, numerous forecasting techniques and their categories have been studied. The goal of this work is to aggregate the findings of several forecasting techniques to aid in the fight against the pandemic. |
format | Online Article Text |
id | pubmed-9886325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98863252023-01-31 Data Mining Based Techniques for Covid-19 Predictions Rane, Rahul Dubey, Aditya Rasool, Akhtar Wadhvani, Rajesh Procedia Comput Sci Article COVID-19 is a pandemic that has resulted in numerous fatalities and infections in recent years, with a rising tendency in both the number of infections and deaths and the pace of recovery. Accurate forecasting models are important for making accurate forecasts and taking relevant actions. As a result, accurate short-term forecasting of the number of new cases that are contaminated and recovered is essential for making the best use of the resources at hand and stopping or delaying the spread of such illnesses. This paper shows the various techniques for forecasting the covid-19 cases. This paper classifies the various models according to their category and shows the merits and demerits of various fore-casting techniques. The research provides insight into potential issues that may arise during the forecasting of covid-19 instances for predicting the positive, negative, and death cases in this pandemic. In this paper, numerous forecasting techniques and their categories have been studied. The goal of this work is to aggregate the findings of several forecasting techniques to aid in the fight against the pandemic. The Author(s). Published by Elsevier B.V. 2023 2023-01-31 /pmc/articles/PMC9886325/ /pubmed/36743794 http://dx.doi.org/10.1016/j.procs.2023.01.003 Text en © 2023 The Author(s). Published by Elsevier B.V. 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 Rane, Rahul Dubey, Aditya Rasool, Akhtar Wadhvani, Rajesh Data Mining Based Techniques for Covid-19 Predictions |
title | Data Mining Based Techniques for Covid-19 Predictions |
title_full | Data Mining Based Techniques for Covid-19 Predictions |
title_fullStr | Data Mining Based Techniques for Covid-19 Predictions |
title_full_unstemmed | Data Mining Based Techniques for Covid-19 Predictions |
title_short | Data Mining Based Techniques for Covid-19 Predictions |
title_sort | data mining based techniques for covid-19 predictions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886325/ https://www.ncbi.nlm.nih.gov/pubmed/36743794 http://dx.doi.org/10.1016/j.procs.2023.01.003 |
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