Applications of machine learning approaches to combat COVID-19: A survey

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dc.authorscopusid56599597000
dc.authorscopusid57202924825
dc.authorscopusid54079882700
dc.authorscopusid57406524200
dc.authorscopusid15043035600
dc.authorscopusid57878591500
dc.authorscopusid56888927800
dc.contributor.authorTiwari Sanju Mishra
dc.contributor.authorDoğan Onur
dc.contributor.authorJabbar M. Akhil
dc.contributor.authorShandilya Shishir K
dc.contributor.authorOrtiz-Rodríguez Fernando
dc.contributor.authorBajpai Sailesh
dc.contributor.authorBanerjee Sourav
dc.date.accessioned2023-03-22T19:47:45Z
dc.date.available2023-03-22T19:47:45Z
dc.date.issued2022
dc.departmentBelirleneceken_US
dc.description.abstractMachine learning (ML) and artificial intelligence (AI) approaches are prominent and well established in the field of health-care informatics. Because they have a more productive ability to predict, they are successfully applied in several health-care applications. ML approaches are needed thanks to the unsatisfactory experience of the novel virus, considerable ambiguity, complicated social circumstances, and inadequate accessible data. Several approaches have been applied as a tool to combat and protect against the new diseases. The COVID-19 outbreak has rapid growth, so it is not easy to predict the patients and resources within a specified time. ML is a strong approach in the fighting against the pandemic such as COVID-19. It is found significant to predict the susceptible, infected, recovered, or exposed persons and can assist the control strategies to block the spread of infections. This study critically examines the appropriateness and contribution of AI/ML methods on COVID-19 datasets, enhancing the understanding to apply these methods for quick analysis and verification of pandemic databases. © 2022 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/B978-0-323-99878-9.00014-5
dc.identifier.endpage287en_US
dc.identifier.isbn9780323998789
dc.identifier.isbn9780323999441
dc.identifier.scopus2-s2.0-85137487019en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage263en_US
dc.identifier.urihttps://doi.org/10.1016/B978-0-323-99878-9.00014-5
dc.identifier.urihttps://hdl.handle.net/20.500.14034/854
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.journalLessons from COVID-19: Impact on Healthcare Systems and Technologyen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectApplicationsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectCOVID-19en_US
dc.subjectMachine learningen_US
dc.subjectPandemicen_US
dc.subjectReviewen_US
dc.titleApplications of machine learning approaches to combat COVID-19: A surveyen_US
dc.typeBook Chapteren_US

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