Application of artificial intelligence and big data for fighting COVID-19 pandemic

JB Awotunde, S Oluwabukonla, C Chakraborty… - Decision Sciences for …, 2022 - Springer
Abstract The coronavirus (COVID-19) pandemic is playing sensitive havoc in socio-
communal systems, humanity and creates economic crises worldwide. Many strategies have …

[HTML][HTML] Deep learning model for forecasting COVID-19 outbreak in Egypt

M Marzouk, N Elshaboury, A Abdel-Latif… - Process Safety and …, 2021 - Elsevier
Abstract The World Health Organization has declared COVID-19 as a global pandemic in
early 2020. A comprehensive understanding of the epidemiological characteristics of this …

Prediction of the morphological evolution of a splashing drop using an encoder–decoder

J Yee, D Igarashi, S Miyatake… - … Learning: Science and …, 2023 - iopscience.iop.org
The impact of a drop on a solid surface is an important phenomenon that has various
implications and applications. However, the multiphase nature of this phenomenon causes …

Epidemiological predictive modeling of COVID-19 infection: development, testing, and implementation on the population of the Benelux union

T Šušteršič, A Blagojević, D Cvetković… - Frontiers in public …, 2021 - frontiersin.org
Since the outbreak of coronavirus disease-2019 (COVID-19), the whole world has taken
interest in the mechanisms of its spread and development. Mathematical models have been …

Harnessing artificial intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the coronavirus disease 2019 pandemic across the …

S Tao, NL Bragazzi, J Wu, B Mellado, JD Kong - Scientific reports, 2022 - nature.com
In the present paper, we aimed to determine the influence of various non-pharmaceutical
interventions (NPIs) enforced during the first wave of COVID-19 across countries on the …

Digital technologies and COVID-19: Reconsidering lockdown exit strategies for Africa

I Chitungo, M Mhango, E Mbunge, M Dzobo… - Pan African Medical …, 2021 - ajol.info
Widespread vaccination provides a means for countries to lift strict COVID-19 restrictions
previously imposed to contain the spread of the disease. However, to date, Africa has …

Hybrid deep learning algorithm for forecasting SARS-CoV-2 daily infections and death cases

F Alqahtani, M Abotaleb, A Kadi, T Makarovskikh… - Axioms, 2022 - mdpi.com
The prediction of new cases of infection is crucial for authorities to get ready for early
handling of the virus spread. Methodology Analysis and forecasting of epidemic patterns in …

[PDF][PDF] Predicting COVID-19 based on environmental factors with machine learning

AB Abdulkareem, NS Sani, S Sahran… - … Automation & Soft …, 2021 - academia.edu
The coronavirus disease 2019 (COVID-19) has infected more than 50 million people in more
than 100 countries, resulting in a major global impact. Many studies on the potential roles of …

Predicting Multidimensional Environmental Factor Trends in Greenhouse Microclimates Using a Hybrid Ensemble Approach

D Xu, L Ren, X Zhang - Journal of Sensors, 2023 - Wiley Online Library
Trend prediction of greenhouse microclimate is crucial, as greenhouse crops are vulnerable
to potential losses resulting from dramatic changes in greenhouse microclimate …

Explainable time-series prediction using a residual network and gradient-based methods

H Choi, C Jung, T Kang, HJ Kim, IY Kwak - IEEE Access, 2022 - ieeexplore.ieee.org
Researchers are employing deep learning (DL) in many fields, and the scope of its
application is expanding. However, because understanding the rationale and validity of DL …