The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges

Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events. Machine...

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Detalles Bibliográficos
Autores principales: Ahmad, Amir, Garhwal, Sunita, Ray, Santosh Kumar, Kumar, Gagan, Malebary, Sharaf Jameel, Barukab, Omar Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399353/
https://www.ncbi.nlm.nih.gov/pubmed/32837183
http://dx.doi.org/10.1007/s11831-020-09472-8
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author Ahmad, Amir
Garhwal, Sunita
Ray, Santosh Kumar
Kumar, Gagan
Malebary, Sharaf Jameel
Barukab, Omar Mohammed
author_facet Ahmad, Amir
Garhwal, Sunita
Ray, Santosh Kumar
Kumar, Gagan
Malebary, Sharaf Jameel
Barukab, Omar Mohammed
author_sort Ahmad, Amir
collection PubMed
description Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events. Machine learning methods have been used to predict the number of confirmed cases of Covid-19. In this paper, we present a detailed review of these research papers. We present a taxonomy that groups them in four categories. We further present the challenges in this field. We provide suggestions to the machine learning practitioners to improve the performance of machine learning methods for the prediction of confirmed cases of Covid-19.
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spelling pubmed-73993532020-08-04 The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges Ahmad, Amir Garhwal, Sunita Ray, Santosh Kumar Kumar, Gagan Malebary, Sharaf Jameel Barukab, Omar Mohammed Arch Comput Methods Eng Original Paper Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events. Machine learning methods have been used to predict the number of confirmed cases of Covid-19. In this paper, we present a detailed review of these research papers. We present a taxonomy that groups them in four categories. We further present the challenges in this field. We provide suggestions to the machine learning practitioners to improve the performance of machine learning methods for the prediction of confirmed cases of Covid-19. Springer Netherlands 2020-08-04 2021 /pmc/articles/PMC7399353/ /pubmed/32837183 http://dx.doi.org/10.1007/s11831-020-09472-8 Text en © CIMNE, Barcelona, Spain 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Ahmad, Amir
Garhwal, Sunita
Ray, Santosh Kumar
Kumar, Gagan
Malebary, Sharaf Jameel
Barukab, Omar Mohammed
The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title_full The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title_fullStr The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title_full_unstemmed The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title_short The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
title_sort number of confirmed cases of covid-19 by using machine learning: methods and challenges
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399353/
https://www.ncbi.nlm.nih.gov/pubmed/32837183
http://dx.doi.org/10.1007/s11831-020-09472-8
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