How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data...

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Detalles Bibliográficos
Autores principales: Bragazzi, Nicola Luigi, Dai, Haijiang, Damiani, Giovanni, Behzadifar, Masoud, Martini, Mariano, Wu, Jianhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246824/
https://www.ncbi.nlm.nih.gov/pubmed/32370204
http://dx.doi.org/10.3390/ijerph17093176
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author Bragazzi, Nicola Luigi
Dai, Haijiang
Damiani, Giovanni
Behzadifar, Masoud
Martini, Mariano
Wu, Jianhong
author_facet Bragazzi, Nicola Luigi
Dai, Haijiang
Damiani, Giovanni
Behzadifar, Masoud
Martini, Mariano
Wu, Jianhong
author_sort Bragazzi, Nicola Luigi
collection PubMed
description SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data can help in handling the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health facility utilization information. The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic.
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spelling pubmed-72468242020-06-10 How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic Bragazzi, Nicola Luigi Dai, Haijiang Damiani, Giovanni Behzadifar, Masoud Martini, Mariano Wu, Jianhong Int J Environ Res Public Health Communication SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data can help in handling the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health facility utilization information. The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic. MDPI 2020-05-02 2020-05 /pmc/articles/PMC7246824/ /pubmed/32370204 http://dx.doi.org/10.3390/ijerph17093176 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Bragazzi, Nicola Luigi
Dai, Haijiang
Damiani, Giovanni
Behzadifar, Masoud
Martini, Mariano
Wu, Jianhong
How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title_full How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title_fullStr How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title_full_unstemmed How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title_short How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
title_sort how big data and artificial intelligence can help better manage the covid-19 pandemic
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246824/
https://www.ncbi.nlm.nih.gov/pubmed/32370204
http://dx.doi.org/10.3390/ijerph17093176
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