Sex prediction with morphometric measurements of first and fifth metatarsal and phalanx obtained from X-ray images by using machine learning algorithms

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dc.authoridOner, Serkan/0000-0002-7802-880X
dc.authoridSECGIN, YUSUF/0000-0002-0118-6711
dc.authoridSahin, Necati Emre/0000-0002-2061-7951
dc.contributor.authorSenol, D.
dc.contributor.authorBodur, F.
dc.contributor.authorSecgin, Y.
dc.contributor.authorBakici, R. S.
dc.contributor.authorSahin, N. E.
dc.contributor.authorToy, S.
dc.contributor.authorOner, S.
dc.date.accessioned2024-09-29T16:09:56Z
dc.date.available2024-09-29T16:09:56Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBackground: The aim of this study is to predict sex with machine learning (ML) algorithms by making morphometric measurements on radiological images of the first and fifth metatarsal and phalanx bones.Materials and methods: In this study, radiologic images of 263 individuals (135 female, 128 male) between the ages of 27 and 60 were analysed retrospectively. The images in digital imaging and communications in medicine (DICOM) format were transferred to personal workstation Radiant DICOM Viewer programme. Length and width measurements of the first and fifth metatarsal and foot phalanx bones were performed on the transferred images. In addition, the ratios of the total length of the first proximal and distal phalanx and length of the first metatarsal and total length of fifth proximal, middle, and distal phalanx and maximum length of fifth metatarsal were calculated.Results: As a result of machine learning algorithms, highest accuracy, specificity, sensitivity, and Matthews correlation coefficient values were found as 0.85, 0.86, 0.85, and 0.71, respectively with decision tree algorithm. It was found that accu racy rates of other algorithms varied between 0.74 and 0.83. Conclusions: As a result of our study, it was found that sex estimation was made with high accuracy rate by using machine learning algorithms on X-ray images of the first and fifth metatarsal and foot phalanx. We think that in cases when pelvis, cranium and long bones are harmed and examination is difficult, bones of the first and fifth metatarsal and foot phalanx can be used for sex estimation. (Folia Morphol 2023; 82, 3: 704-711)en_US
dc.identifier.doi10.5603/FM.a2022.0052
dc.identifier.endpage711en_US
dc.identifier.issn0015-5659
dc.identifier.issn1644-3284
dc.identifier.issue3en_US
dc.identifier.pmid35607870en_US
dc.identifier.scopus2-s2.0-85169300001en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage704en_US
dc.identifier.urihttps://doi.org/10.5603/FM.a2022.0052
dc.identifier.urihttps://hdl.handle.net/20.500.14619/7857
dc.identifier.volume82en_US
dc.identifier.wosWOS:001060572500001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherVia Medicaen_US
dc.relation.ispartofFolia Morphologicaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectdecision treeen_US
dc.subjectmachine learning algorithmsen_US
dc.subjectmetatarsusen_US
dc.subjectphalanxen_US
dc.subjectradiographyen_US
dc.subjectsex predictionen_US
dc.subjectX-rayen_US
dc.titleSex prediction with morphometric measurements of first and fifth metatarsal and phalanx obtained from X-ray images by using machine learning algorithmsen_US
dc.typeArticleen_US

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