Sex determination by the machine learning algorithms through using morphometric measurements of the carpal, metacarpal, and phalangeal bones

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dc.authorid0000-0001-5587-1055en_US
dc.authorid0000-0002-9218-6468en_US
dc.authorid0000-0002-8124-6402en_US
dc.authorid0000-0002-0417-1806en_US
dc.contributor.authorŞenol, Gamze Taşkın
dc.contributor.authorKürtül, İbrahim
dc.contributor.authorRay, Abdullah
dc.contributor.authorAhmetoğlu, Gülçin
dc.date.accessioned2024-05-28T11:40:24Z
dc.date.available2024-05-28T11:40:24Z
dc.date.issued2023en_US
dc.departmentBAİBÜ, Tıp Fakültesi, Temel Tıp Bilimleri Bölümüen_US
dc.description.abstractIn the study, it was aimed to predict sex from hand measurements using machine learning algorithms (MLA). Measurements were made on MR images of 60 men and 60 women. Determined parameters; hand length (HL), palm length (PL), hand width (HW), wrist width (EBG), metacarpal I length (MIL), metacarpal I width (MIW), metacarpal II length (MIIL), metacarpal II width (MIIW), metacarpal III length (MIIL), metacarpal III width (MIIIW), metacarpal IV length (MIVL), metacarpal IV width (MIVW), metacarpal V length (MVL), metacarpal V width (MVW), phalanx I length (PILL), measured as phalanx II length (PIIL), phalanx III length (PIIL), phalanx IV length (PIVL), phalanx V length (PVL). In addition, the hand index (HI) was calculated. Logistic Regression (LR), Random Forest (RF), Linear Discriminant Analysis (LDA), K-nearest neighbour (KNN) and Naive Bayes (NB) were used as MLAs. In the study, the KNN algorithm's Accuracy, SEN, F1 and Specificity ratios were determined as 88 %. In this study using MLA, it is understood that the highest accuracy belongs to the KNN algorithm. Except for the hand's MIIW, MIIIW, MIVW, MVW, HI variables, other variables were statistically significant in terms of sex difference.en_US
dc.identifier.citationSenol, G. T., Kürtül, I., Ray, A., & Ahmetoglu, G. (2023). Sex Determination by the Machine Learning Algorithms Through Using Morphometric Measurements of the Carpal, Metacarpal, and Phalangeal Bones. International Journal of Morphology, 41(4).en_US
dc.identifier.endpage1272en_US
dc.identifier.issn0717-9502
dc.identifier.issn0717-9367
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85169421080en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1267en_US
dc.identifier.urihttps://www.webofscience.com/wos/woscc/full-record/WOS:001048344800041
dc.identifier.urihttps://hdl.handle.net/20.500.12491/12177
dc.identifier.volume41en_US
dc.identifier.wosWOS:001048344800041en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorŞenol, Gamze Taşkın
dc.institutionauthorKürtül, İbrahim
dc.institutionauthorRay, Abdullah
dc.institutionauthorAhmetoğlu, Gülçin
dc.language.isoenen_US
dc.publisherSociedad Chilena de Anatomíaen_US
dc.relation.ispartofInternational Journal of Morphologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHanden_US
dc.subjectSex Determinationen_US
dc.subjectMagnetic Resonance Imagingen_US
dc.subjectStatureen_US
dc.subjectLengthen_US
dc.subjectFooten_US
dc.titleSex determination by the machine learning algorithms through using morphometric measurements of the carpal, metacarpal, and phalangeal bonesen_US
dc.typeArticleen_US

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