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dc.creatorSwapnarekha, H.
dc.creatorSekhar Behera, Himansu
dc.creatorNayak, Janmenjoy
dc.creatorNaik, Bighnaraj
dc.date.accessioned2020-07-23T19:08:21Z
dc.date.available2020-07-23T19:08:21Z
dc.date.created2020-05-29
dc.identifier.issn0960-0779spa
dc.identifier.otherhttps://www.sciencedirect.com/science/article/pii/S0960077920303465?via%3Dihub#!spa
dc.identifier.urihttp://hdl.handle.net/20.500.12010/11056
dc.format.extent15 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.publisherChaos, Solitons & Fractalseng
dc.sourcereponame:Expeditio Repositorio Institucional UJTLspa
dc.sourceinstname:Universidad de Bogotá Jorge Tadeo Lozanospa
dc.subjectMachine learningspa
dc.subjectStatistical methodsspa
dc.subjectDeep learningspa
dc.titleRole of intelligent computing in COVID-19 prognosis: A state-of-the-art reviewspa
dc.type.localArtículospa
dc.subject.lembSíndrome respiratorio agudo gravespa
dc.subject.lembCOVID-19spa
dc.subject.lembSARS-CoV-2spa
dc.subject.lembCoronavirusspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersionspa
dc.identifier.doihttps://doi.org/10.1016/j.chaos.2020.109947spa
dc.description.abstractenglishThe World Health Organization (WHO) declared novel coronavirus 2019 (COVID-19), an infectious epidemic caused by SARS-CoV-2, as Pandemic in March 2020. It has affected more than 40 million people in 216 countries. Almost in all the affected countries, the number of infected and deceased patients has been enhancing at a distressing rate. As the early prediction can reduce the spread of the virus, it is highly desirable to have intelligent prediction and diagnosis tools. The inculcation of efficient forecasting and prediction models may assist the government in implementing better design strategies to prevent the spread of virus. In this paper, a state-of-the-art analysis of the ongoing machine learning (ML) and deep learning (DL) methods in the diagnosis and prediction of COVID-19 has been done. Moreover, a comparative analysis on the impact of machine learning and other competitive approaches like mathematical and statistical models on COVID-19 problem has been conducted. In this study, some factors such as type of methods(machine learning, deep learning, statistical & mathematical) and the impact of COVID research on the nature of data used for the forecasting and prediction of pandemic using computing approaches has been presented. Finally some important research directions for further research on COVID-19 are highlighted which may facilitate the researchers and technocrats to develop competent intelligent models for the prediction and forecasting of COVID-19 real time data.spa


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