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Detection of Rheumatoid Arthritis From Hand Radiographs Using A Convolutional Neural Network

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dc.contributor.author Üreten, K.
dc.contributor.author Erbay, H.
dc.contributor.author Maraş, H. Hakan
dc.date.accessioned 2020-05-20T19:34:07Z
dc.date.available 2020-05-20T19:34:07Z
dc.date.issued 2020-04-01
dc.identifier.citation Üreten, K.; Erbay, H.; Maraş, H.H., "Detection of Rheumatoid Arthritis From Hand Radiographs Using A Convolutional Neural Network", Clinical Rheumatology, Vol. 39, No. 4, pp. 969-974, (2020). tr_TR
dc.identifier.issn 07703198
dc.identifier.uri http://hdl.handle.net/20.500.12416/3970
dc.description.abstract Introduction: Plain hand radiographs are the first-line and most commonly used imaging methods for diagnosis or differential diagnosis of rheumatoid arthritis (RA) and for monitoring disease activity. In this study, we used plain hand radiographs and tried to develop an automated diagnostic method using the convolutional neural networks to help physicians while diagnosing rheumatoid arthritis. Methods: A convolutional neural network (CNN) is a deep learning method based on a multilayer neural network structure. The network was trained on a dataset containing 135 radiographs of the right hands, of which 61 were normal and 74 RA, and tested it on 45 radiographs, of which 20 were normal and 25 RA. Results: The accuracy of the network was 73.33% and the error rate 0.0167. The sensitivity of the network was 0.6818; the specificity was 0.7826 and the precision 0.7500. Conclusion: Using only pixel information on hand radiographs, a multi-layer CNN architecture with online data augmentation was designed. The performance metrics such as accuracy, error rate, sensitivity, specificity, and precision state shows that the network is promising in diagnosing rheumatoid arthritis. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer tr_TR
dc.relation.isversionof 10.1007/s10067-019-04487-4 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Deep Learning tr_TR
dc.subject Convolutional Neural Network tr_TR
dc.subject Plain Hand Radiographs tr_TR
dc.subject Rheumatoid Arthritis tr_TR
dc.title Detection of Rheumatoid Arthritis From Hand Radiographs Using A Convolutional Neural Network tr_TR
dc.type article tr_TR
dc.relation.journal Clinical Rheumatology tr_TR
dc.identifier.volume 39 tr_TR
dc.identifier.issue 4 tr_TR
dc.identifier.startpage 969 tr_TR
dc.identifier.endpage 974 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR


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