Covid-19 Disease Diagnosis from Radiology Data with Deep Learning Algorithms

dc.contributor.authorMertyuz, Irem
dc.contributor.authorMertyuz, Tolga
dc.contributor.authorTasar, Beyda
dc.contributor.authorYakut, Oguz
dc.date.accessioned2026-08-12T16:09:01Z
dc.date.issued2020
dc.departmentFırat Üniversitesi
dc.description4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- Istanbul -- 165025
dc.description.abstractSince December 2019, the COVID-19 coronavirus epidemic has spread around the world. In the face of this epidemic, it is important to speed up the diagnosis of the disease in order to reduce the loss of life and to prevent the epidemic from spreading. One of the methods used to diagnose disease is to analyze computed tomography images. In this study, a deep learning algorithm has been developed for disease diagnosis by analysis of computed tomography images. A data set consisting of computerized images of patients with COVID-19, Normal and Pneumonia was used. The results of algorithms with three different network structures are compared. © 2020 IEEE.
dc.identifier.doi10.1109/ISMSIT50672.2020.9255380
dc.identifier.isbn978-172819090-7
dc.identifier.scopus2-s2.0-85097674554
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ISMSIT50672.2020.9255380
dc.identifier.urihttps://hdl.handle.net/11508/41538
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectCOVID-19 Disease Diagnosis; Deep Learning; GoogleNet; ResNet; VGG-16
dc.titleCovid-19 Disease Diagnosis from Radiology Data with Deep Learning Algorithms
dc.typeConference Object

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