Y Covid-19 Classification Using Deep Learning in Chest X-Ray Images

dc.contributor.authorKarhan, Zehra
dc.contributor.authorAkal, Fuat
dc.date.accessioned2024-02-23T14:45:03Z
dc.date.available2024-02-23T14:45:03Z
dc.date.issued2020
dc.departmentNEÜen_US
dc.description2020 Medical Technologies Congress (TIPTEKNO) -- NOV 19-20, 2020 -- ELECTR NETWORKen_US
dc.description.abstractCovid-19 virus, which has emerged in the Republic of China in an undetermined cause, has affected the whole world quickly. It is important to detect positive cases early to prevent further spread of the outbreak. In the diagnostic phase, radiological images of the chest are determinative as well as the RT-PCR (Reverse Transcription-Polymerase Chain Reaction) test. It was classified with the ResNet50 model, which is a convolutional neural network architecture in Covid-19 detection using chest x-ray images. Chest X-Ray image analysis can be done and infected individuals can be identified thanks to artificial intelligence quickly. The experimental results are encouraging in terms of the use of computer-aided in the field of pathology. It can also be used in situations where the possibilities and RT-PCR tests are insufficient.en_US
dc.description.sponsorshipBiyomedikal ve Klinik Muhendisligi Dernegi,Izmir Ekonomi Univ,Izmir Katip Celebi Univen_US
dc.identifier.isbn978-1-7281-8073-1
dc.identifier.urihttps://hdl.handle.net/20.500.12452/17231
dc.identifier.wosWOS:000659419900096en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2020 Medical Technologies Congress (Tiptekno)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChest X-Ray Imagesen_US
dc.subjectCoronavirusen_US
dc.subjectCuvid-19en_US
dc.subjectDeep Learningen_US
dc.subjectTransfer Learningen_US
dc.titleY Covid-19 Classification Using Deep Learning in Chest X-Ray Imagesen_US
dc.typeConference Objecten_US

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