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A review on machine learning approaches in COVID-19 pandemic prediction and forecasting

Novel COVID-19 Coronavirus disease, namely SARS-CoV-2, is a global pandemic and has spread to more than 200 countries. The sudden rise in the number of cases is causing a tremendous effect on healthcare services worldwide. To assist strategies in containing its spread, machine learning (ML) has been...

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Main Authors: Nazirun, Nor Nisha Nadhira, Omar, Nashuha, Selvaganeson, Koshelya, Abdul Wahab, Asnida
Format: Article
Published: Universiti Putra Malaysia Press 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/99439/
http://dx.doi.org/10.47836/mjmhs.18.s6.14
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spelling my.utm.994392023-02-27T04:27:32Z http://eprints.utm.my/id/eprint/99439/ A review on machine learning approaches in COVID-19 pandemic prediction and forecasting Nazirun, Nor Nisha Nadhira Omar, Nashuha Selvaganeson, Koshelya Abdul Wahab, Asnida TK Electrical engineering. Electronics Nuclear engineering Novel COVID-19 Coronavirus disease, namely SARS-CoV-2, is a global pandemic and has spread to more than 200 countries. The sudden rise in the number of cases is causing a tremendous effect on healthcare services worldwide. To assist strategies in containing its spread, machine learning (ML) has been employed to effectively track the daily infected and mortality cases as well as to predict the peak growth among the states or/and country-wise. The evidence of ML in tackling previous epidemics has encouraged researchers to reciprocate with this outbreak. In this paper, recent studies that apply various ML models in predicting and forecasting COVID-19 trends have been reviewed. The development in ML has significantly supported health experts with improved prediction and forecasting. By developing prediction models, the world can prepare and mitigate the spread and impact against COVID-19. Universiti Putra Malaysia Press 2022 Article PeerReviewed Nazirun, Nor Nisha Nadhira and Omar, Nashuha and Selvaganeson, Koshelya and Abdul Wahab, Asnida (2022) A review on machine learning approaches in COVID-19 pandemic prediction and forecasting. Malaysian Journal of Medicine and Health Sciences, 18 . pp. 78-84. ISSN 1675-8544 http://dx.doi.org/10.47836/mjmhs.18.s6.14 DOI : 10.47836/mjmhs.18.s6.14
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Nazirun, Nor Nisha Nadhira
Omar, Nashuha
Selvaganeson, Koshelya
Abdul Wahab, Asnida
A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
description Novel COVID-19 Coronavirus disease, namely SARS-CoV-2, is a global pandemic and has spread to more than 200 countries. The sudden rise in the number of cases is causing a tremendous effect on healthcare services worldwide. To assist strategies in containing its spread, machine learning (ML) has been employed to effectively track the daily infected and mortality cases as well as to predict the peak growth among the states or/and country-wise. The evidence of ML in tackling previous epidemics has encouraged researchers to reciprocate with this outbreak. In this paper, recent studies that apply various ML models in predicting and forecasting COVID-19 trends have been reviewed. The development in ML has significantly supported health experts with improved prediction and forecasting. By developing prediction models, the world can prepare and mitigate the spread and impact against COVID-19.
format Article
author Nazirun, Nor Nisha Nadhira
Omar, Nashuha
Selvaganeson, Koshelya
Abdul Wahab, Asnida
author_facet Nazirun, Nor Nisha Nadhira
Omar, Nashuha
Selvaganeson, Koshelya
Abdul Wahab, Asnida
author_sort Nazirun, Nor Nisha Nadhira
title A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
title_short A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
title_full A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
title_fullStr A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
title_full_unstemmed A review on machine learning approaches in COVID-19 pandemic prediction and forecasting
title_sort review on machine learning approaches in covid-19 pandemic prediction and forecasting
publisher Universiti Putra Malaysia Press
publishDate 2022
url http://eprints.utm.my/id/eprint/99439/
http://dx.doi.org/10.47836/mjmhs.18.s6.14
_version_ 1758966898145361920
score 13.160551

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