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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.
  • Bragazzi NL; Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.
  • Dai H; Postgraduate School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, 16132 Genoa, Italy.
  • Damiani G; Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.
  • Behzadifar M; Department of Dermatology, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Martini M; Clinical Dermatology, I.R.C.C.S. Istituto Ortopedico Galeazzi, 20161 Milan, Italy.
  • Wu J; Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy.
Int J Environ Res Public Health ; 17(9)2020 05 02.
Article in English | MEDLINE | ID: covidwho-1725599
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Artificial Intelligence / Coronavirus Infections / Pandemics / Big Data Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Year: 2020 Document Type: Article Affiliation country: Ijerph17093176

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Artificial Intelligence / Coronavirus Infections / Pandemics / Big Data Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Year: 2020 Document Type: Article Affiliation country: Ijerph17093176