A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of
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A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of COVID-19 Youssoufa Mohamadou1,2
· Aminou Halidou3 · Pascalin Tiam Kapen2,4,5
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In the past few months, several works were published in regards to the dynamics and early detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of this work is to provide the research community with comprehensive overview of the methods used in these studies as well as a compendium of available open source datasets in regards to COVID-19. In all, 61 journal articles, reports, fact sheets, and websites dealing with COVID-19 were studied and reviewed. It was found that most mathematical modeling done were based on the Susceptible-Exposed-Infected-Removed (SEIR) and Susceptible-infected-recovered (SIR) models while most of the AI implementations were Convolutional Neural Network (CNN) on X-ray and CT images. In terms of available datasets, they include aggregated case reports, medical images, management strategies, healthcare workforce, demography, and mobility during the outbreak. Both Mathematical modeling and AI have both shown to be reliable tools in the fight against this pandemic. Several datasets concerning the COVID-19 have also been collected and shared open source. However, much work is needed to be done in the diversification of the datasets. Other AI and modeling applications in healthcare should be explored in regards to this COVID-19. Keywords COVID-19 · Corona virus · Mathematical modeling · Artificial intelligence · Open source dataset
1 Introduction The World Health Organization declared that new coronavirus disease 2019 (COVID-19) was a Public Health
This article belongs to the Topical Collection: Artificial Intelligence Applications for COVID-19, Detection, Control, Prediction, and Diagnosis Youssoufa Mohamadou
[email protected] 1
University Institute of Technology, University of Ngaoundere, P.O Box 454, Ngaoundere, Cameroon
2
BEEMo Lab, ISST, Universit´e des Montagnes, P.O. Box 208 Bangangt´e, Cameroon
3
Department of Computer Science, University of Yaounde I, 812, Yaounde, Cameroon
4
URISIE, University Institute of Technology Fotso Victor, University of Dschang, P.O Box 134, Bandjoun, Cameroon
5
UR2MSP, Department of Physics, University of Dschang, P.O Box 67, Dschang, Cameroon
Emergency of International Concern on January 30th 2020 [1, 2]. By then there were a total number of 7818 confirmed cases of COVID-19 globally with more than 1370 severe cases and 170 deaths. The bulk of which was found in China [3]. Over the course of a few weeks the disease has propagated across the boundaries of China infecting nearly every country. At the time of writing this paper (May 01, 2020) there is a total of 2,397,216 confirmed cases globally with 162,956 deaths [4]. Symptoms of the disease include dry cough, sore throat, and fever. Although the majority of the cases are mild, some cases
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