Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning

This book chapter presents the review of COVID-19 and its status, as well as the scientific Analysis big data analytics with the help of machine learning. We provide in-depth literature review, and provide a summary of the current AI and machine learning methods, which have become increasingly impor...

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Detalles Bibliográficos
Autores principales: Chang, Victor, Ali, Mohamed Aleem, Hossain, Alamgir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069062/
http://dx.doi.org/10.1016/B978-0-323-90054-6.00007-6
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author Chang, Victor
Ali, Mohamed Aleem
Hossain, Alamgir
author_facet Chang, Victor
Ali, Mohamed Aleem
Hossain, Alamgir
author_sort Chang, Victor
collection PubMed
description This book chapter presents the review of COVID-19 and its status, as well as the scientific Analysis big data analytics with the help of machine learning. We provide in-depth literature review, and provide a summary of the current AI and machine learning methods, which have become increasingly important to provide accurate analyses. Various conceptual diagrams have been used to illustrate how different technologies can contribute to effective analyses for COVID-19. We demonstrate our work from both theoretical contributions and practical implementations.
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spelling pubmed-90690622022-05-04 Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning Chang, Victor Ali, Mohamed Aleem Hossain, Alamgir Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 Article This book chapter presents the review of COVID-19 and its status, as well as the scientific Analysis big data analytics with the help of machine learning. We provide in-depth literature review, and provide a summary of the current AI and machine learning methods, which have become increasingly important to provide accurate analyses. Various conceptual diagrams have been used to illustrate how different technologies can contribute to effective analyses for COVID-19. We demonstrate our work from both theoretical contributions and practical implementations. 2022 2022-04-08 /pmc/articles/PMC9069062/ http://dx.doi.org/10.1016/B978-0-323-90054-6.00007-6 Text en Copyright © 2022 Elsevier Inc. All rights reserved. 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
Chang, Victor
Ali, Mohamed Aleem
Hossain, Alamgir
Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title_full Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title_fullStr Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title_full_unstemmed Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title_short Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
title_sort investigation of covid-19 and scientific analysis big data analytics with the help of machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069062/
http://dx.doi.org/10.1016/B978-0-323-90054-6.00007-6
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