Detection of rheumatoid arthritis from hand radiographs using a convolutional neural network

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dc.contributor.authorUreten, Kemal
dc.contributor.authorErbay, Hasan
dc.contributor.authorMaras, Hadi Hakan
dc.date.accessioned2021-01-14T18:10:44Z
dc.date.available2021-01-14T18:10:44Z
dc.date.issued2020
dc.departmentKKÜ
dc.description.abstractIntroduction 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.en_US
dc.identifier.citationBu makale açık erişimli değildir.en_US
dc.identifier.doi10.1007/s10067-019-04487-4
dc.identifier.endpage974en_US
dc.identifier.issn0770-3198
dc.identifier.issn1434-9949
dc.identifier.issue4en_US
dc.identifier.pmid30850962
dc.identifier.scopus2-s2.0-85062710388
dc.identifier.scopusqualityQ1
dc.identifier.startpage969en_US
dc.identifier.urihttps://doi.org/10.1007/s10067-019-04487-4
dc.identifier.urihttps://hdl.handle.net/20.500.12587/12754
dc.identifier.volume39en_US
dc.identifier.wosWOS:000524870500001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSPRINGER LONDON LTDen_US
dc.relation.ispartofCLINICAL RHEUMATOLOGY
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectConvolutional neural networken_US
dc.subjectDeep learningen_US
dc.subjectPlain hand radiographsen_US
dc.subjectRheumatoid arthritisen_US
dc.titleDetection of rheumatoid arthritis from hand radiographs using a convolutional neural networken_US
dc.typeArticle

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