Efficient estimation of osteoporosis using Artificial Neural Networks

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dc.contributor.authorLemineur, Gerald
dc.contributor.authorHarba, Rachid
dc.contributor.authorKılıç, Niyazi
dc.contributor.authorUçan, Osman N.
dc.contributor.authorOsman, Onur
dc.contributor.authorBenhamou, Laurent
dc.date.accessioned2020-11-21T15:56:33Z
dc.date.available2020-11-21T15:56:33Z
dc.date.issued2007en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description33rd Annual Conference of the IEEE Industrial Electronics Society, IECON -- 5 November 2007 through 8 November 2007 -- Taipei -- 73038en_US
dc.description.abstractIn this communication, Artificial Neural Network (ANN) is applied to discriminate osteoporotic fracture and control cases in a group of 304 patients. ANN is one of the popular methods in optimization of complex engineering problems compared to the classical statistical methods. In our study group, we consider some parameters as inputs: three bone densitometry parameters (HMD) (Femoral neck BMD, Total Body BMD and L2L4 spine BMD), three fractal parameters [1,5] (Hmin. Hmean, Hmax), and age of the patient. We studied three ANN structures with various inputs and hidden neurons. We have reached up to 81.66% correct classification. In comparison we have tested a classical discriminant analysis (Mahalanobis-Fisher) and we only obtained 72% of correct classification. We can conclude that ANN is one of the promising methods in the diagnosis of osteoporosis. ©2007 IEEE.en_US
dc.identifier.doi10.1109/IECON.2007.4460070en_US
dc.identifier.endpage3044en_US
dc.identifier.issn1424407834; 9781424407835
dc.identifier.scopus2-s2.0-49949097778en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage3039en_US
dc.identifier.urihttps://doi.org/10.1109/IECON.2007.4460070
dc.identifier.urihttps://hdl.handle.net/11467/4149
dc.identifier.wosWOS:000253451402173en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofIECON Proceedings (Industrial Electronics Conference)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleEfficient estimation of osteoporosis using Artificial Neural Networksen_US
dc.typeConference Objecten_US

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