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.

How big data and artificial intelligence can help better manage the covid-19 pandemic / N.L. Bragazzi, H. Dai, G. Damiani, M. Behzadifar, M. Martini, J. Wu. - In: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. - ISSN 1661-7827. - 17:9(2020), pp. 3176.1-3176.10. [10.3390/ijerph17093176]

How big data and artificial intelligence can help better manage the covid-19 pandemic

G. Damiani
Validation
;
2020

Abstract

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.
Artificial intelligence; Big Data; Epidemiology; Public health; Viral outbreak; Coronavirus Infections; Humans; Pandemics; Pneumonia, Viral; Randomized Controlled Trials as Topic; Artificial Intelligence; Big Data
Settore MED/35 - Malattie Cutanee e Veneree
2020
Article (author)
File in questo prodotto:
File Dimensione Formato  
ijerph-17-03176-v2.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 302.94 kB
Formato Adobe PDF
302.94 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/787887
Citazioni
  • ???jsp.display-item.citation.pmc??? 65
  • Scopus 241
  • ???jsp.display-item.citation.isi??? 182
social impact