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dc.contributor.authorAlsharif, Mohammed H.
dc.contributor.authorAlsharif, Yahia H.
dc.contributor.authorYahya, Khalid O. Moh.
dc.contributor.authorAlomari, Osama Ahmad
dc.contributor.authorAlbreem, Mahmoud A. M.
dc.contributor.authorJahid, Abu
dc.date.accessioned2023-08-18T10:39:24Z
dc.date.available2023-08-18T10:39:24Z
dc.date.issued2020en_US
dc.identifier.issn1128-3602
dc.identifier.urihttps://hdl.handle.net/11363/5373
dc.description.abstractRecent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. Reverse transcription-polymerase chain reaction (RTPCR) is known as one of the primary diagnostic tools. However, RT-PCR tests are costly and time-consuming; it also requires specific materials, equipment, and instruments. Moreover, most countries are suffering from a lack of testing kits because of limitations on budget and techniques. Thus, this standard method is not suitable to meet the requirements of fast detection and tracking during the COVID-19 pandemic, which motived to employ deep learning (DL)/ convolutional neural networks (CNNs) technology with X-ray and CT scans for efficient analysis and diagnostic. This study provides insight about the literature that discussed the deep learning technology and its various techniques that are recently developed to combat the dissemination of COVID-19 disease.en_US
dc.language.isoengen_US
dc.publisherVERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALYen_US
dc.relation.isversionof10.26355/eurrev_202011_23640en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectArtificial intelligenceen_US
dc.subjectCoronavirus pandemicen_US
dc.subjectAIen_US
dc.subjectSARS-CoV-2en_US
dc.subjectMachine learningen_US
dc.subjectBig dataen_US
dc.subjectCOVID-19en_US
dc.titleDeep learning applications to combat the dissemination of COVID-19 disease: a reviewen_US
dc.typearticleen_US
dc.relation.ispartofEuropean Review for Medical and Pharmacological Sciencesen_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.authoridhttps://orcid.org/0000-0001-8579-5444en_US
dc.authoridhttps://orcid.org/0000-0002-0792-7031en_US
dc.authoridhttps://orcid.org/0000-0002-6464-1101en_US
dc.identifier.volume24en_US
dc.identifier.issue21en_US
dc.identifier.startpage11455en_US
dc.identifier.endpage11460en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorYahya, Khalid O. Moh.
dc.contributor.institutionauthorAlomari, Osama Ahmad


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