Artificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issues

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dc.authoridhttps://orcid.org/0000-0001-8579-5444en_US
dc.authoridhttps://orcid.org/0000-0002-9321-6956en_US
dc.authoridhttps://orcid.org/0000-0002-6464-1101en_US
dc.contributor.authorAlsharif, Mohammed H.
dc.contributor.authorAlsharif, Yahia H.
dc.contributor.authorChaudhry, Shehzad Ashraf
dc.contributor.authorAlbreem, Mahmoud A. M.
dc.contributor.authorJahid, Abu
dc.contributor.authorHwang, Eenjun
dc.date.accessioned2023-08-17T07:52:19Z
dc.date.available2023-08-17T07:52:19Z
dc.date.issued2020en_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.description.abstractToday, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. In this study, the early diagnosis of this disease through artificial intelligence (AI) technology is explored. AI is a revolutionizing technology that drives new research opportunities in various fields. Although this study does not provide a final solution, it highlights the most promising lines of research on AI technology for the diagnosis of COVID-19. The major contribution of this work is a discussion on the following substantial issues of AI technology for preventing the severe effects of COVID-19: (1) rapid diagnosis and detection, (2) outbreak and prediction of virus spread, and (3) potential treatments. This study profoundly investigates these controversial research topics to achieve a precise, concrete, and concise conclusion. Thus, this study provides significant recommendations on future research directions related to COVID-19.en_US
dc.identifier.doi10.26355/eurrev_202009_22875en_US
dc.identifier.endpage9233en_US
dc.identifier.issn1128-3602
dc.identifier.issue17en_US
dc.identifier.pmid32965018en_US
dc.identifier.scopus2-s2.0-85091587499en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage9226en_US
dc.identifier.urihttps://hdl.handle.net/11363/5362
dc.identifier.urihttps://doi.org/
dc.identifier.volume24en_US
dc.identifier.wosWOS:000569313100081en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorChaudhry, Shehzad Ashraf
dc.language.isoenen_US
dc.publisherVERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALYen_US
dc.relation.ispartofEuropean Review for Medical and Pharmacological Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_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.subjectCOVID-19en_US
dc.subjectMachine learningen_US
dc.subjectBig dataen_US
dc.titleArtificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issuesen_US
dc.typeArticleen_US

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