Estimation of the femur length from its proximal measurements in Anatolian Caucasians by artificial neural networks

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dc.authoridotag, aynur -- 0000-0002-8242-0177; Otag, Ilhan -- 0000-0002-3794-4668en_US
dc.contributor.authorOtag, Ilhan
dc.contributor.authorOtag, Aynur
dc.contributor.authorAkkoyun, Serkan
dc.contributor.authorCimen, Mehmet
dc.date.accessioned2019-07-27T12:10:23Z
dc.date.accessioned2019-07-28T09:45:20Z
dc.date.available2019-07-27T12:10:23Z
dc.date.available2019-07-28T09:45:20Z
dc.date.issued2016
dc.department[Otag, Ilhan -- Akkoyun, Serkan] Cumhuriyet Univ, Vocat Sch Hlth, Sivas, Turkey -- [Otag, Aynur] Cumhuriyet Univ, Fac Hlth Sci, Sivas, Turkey -- [Cimen, Mehmet] Cumhuriyet Univ, Dept Anat, Fac Med, Sivas, Turkeyen_US
dc.description.abstractFemora are a well preserved section of the skeleton after death. Therefore, they are commonly used in the field of forensic sciences, physical anthropology and anatomy. In addition, femur morphometry is helpful in finding sex or side (left or right) differences. The femur also shows characteristics of certain populations. Femur length is important for calculation of individual stature. In this study, the artificial neural network method was used to estimate femur length. In total, 230 femora exemplar were used. The three input parameters of the method were the distance between trochanter major top point and trochanter minor bottom point, the diameter of caput femoris and the diameter of collum femoris. By using these parameters, the artificial neural network estimation on femur length was performed. The results show that the method is capable of performing this estimation. In addition, sex discrimination was performed and achieved with 82% accuracy. As well as the identification of sex or side differences, morphometry of the proximal femur is necessary and important for surgical procedures.en_US
dc.identifier.doi10.1080/00450618.2015.1004193en_US
dc.identifier.endpage286en_US
dc.identifier.issn0045-0618
dc.identifier.issn1834-562X
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-84923038264en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage279en_US
dc.identifier.urihttps://dx.doi.org/10.1080/00450618.2015.1004193
dc.identifier.urihttps://hdl.handle.net/20.500.12418/7311
dc.identifier.volume48en_US
dc.identifier.wosWOS:000375919600006en_US
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS LTDen_US
dc.relation.ispartofAUSTRALIAN JOURNAL OF FORENSIC SCIENCESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfemuren_US
dc.subjectmorphometryen_US
dc.subjectsexual dimorphismen_US
dc.subjectartificial neural networken_US
dc.titleEstimation of the femur length from its proximal measurements in Anatolian Caucasians by artificial neural networksen_US
dc.typeArticleen_US

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