Cloud and IoMT-Based Big Data Analytics System During COVID-19 Pandemic

Author:

Awotunde Joseph BamideleORCID,Ogundokun Roseline OluwaseunORCID,Misra Sanjay

Publisher

Springer International Publishing

Reference75 articles.

1. R.O. Ogundokun, J.B. Awotunde, Machine learning prediction for COVID-19 pandemic in India. medRxiv (2020)

2. M.É. Czeisler, M.E. Howard, R. Robbins, L.K. Barger, E.R. Facer-Childs, S.M. Rajaratnam, C.A. Czeisler, Early public adherence with and support for stay-at-home COVID-19 mitigation strategies despite adverse life impact: A transnational cross-sectional survey study in the United States and Australia. BMC Public Health 21(1), 1–16 (2021)

3. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) (2020), https://coronavirus.jhu.edu/map.html. Last accessed 1 Sept 2020

4. D. Dunford, B. Dale, N.L. Stylianou, M. Ahmed, I.d.l.T. Arenas, Coronavirus: The world in lockdown in maps and charts. BBC News (2020). Available at https://www.BBC.com/news/world-52103747

5. R.O. Ogundokun, A.F. Lukman, G.B. Kibria, J.B. Awotunde, B.B. Aladeitan, Predictive modelling of COVID-19 confirmed cases in Nigeria. Infect. Dis. Model. 5, 543–548 (2020)

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