Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networks

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dc.authoridSECGIN, YUSUF/0000-0002-0118-6711
dc.contributor.authorSenol, D.
dc.contributor.authorBodur, F.
dc.contributor.authorSecgin, Y.
dc.contributor.authorSencan, D.
dc.contributor.authorDuman, Sb
dc.contributor.authorOner, Z.
dc.date.accessioned2024-09-29T16:08:28Z
dc.date.available2024-09-29T16:08:28Z
dc.date.issued2024
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBackground:Sex determination from the bones is of great importance for forensic medicine and anthropology. The mandible is highly valued because it is the strongest, largest and most dimorphic bone in the skull.Aim:Our aim in this study is gender estimation with morphometric measurements taken from mandibular lingula, an important structure on the mandible, by using machine learning algorithms and artificial neural networks.Methods:Cone beam computed tomography images of the mandibular lingula were obtained by retrospective scanning from the Picture Archiving Communication Systems of the Department of Oral, Dental and Maxillofacial Radiology, Faculty of Dentistry, & Idot;n & ouml;n & uuml; University. Images scanned in Digital Imaging and Communications in Medicine (DICOM) format were transferred to RadiAnt DICOM Viewer (Version: 2020.2). The images were converted to 3-D format by using the 3D Volume Rendering console of the program. Eight anthropometric parameters were measured bilaterally from these 3-D images based on the mandibular lingula.Results:The results of the machine learning algorithms analyzed showed that the highest accuracy was 0.88 with Random Forest and Gaussian Naive Bayes algorithm. Accuracy rates of other parameters ranged between 0.78 and 0.88.Conclusions:As a result of the study, it is thought that mandibular lingula-centered morphometric measurements can be used for gender determination as well as bones such as the pelvis and skull as they were found to be highly accurate. This study also provides information on the anatomical position of the lingula according to gender in Turkish society. The results can be important for oral-dental surgeons, anthropologists, and forensic experts.en_US
dc.identifier.doi10.4103/njcp.njcp_787_23
dc.identifier.endpage738en_US
dc.identifier.issn1119-3077
dc.identifier.issn2229-7731
dc.identifier.issue6en_US
dc.identifier.pmid38943297en_US
dc.identifier.scopus2-s2.0-85197176598en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage732en_US
dc.identifier.urihttps://doi.org/10.4103/njcp.njcp_787_23
dc.identifier.urihttps://hdl.handle.net/20.500.14619/7560
dc.identifier.volume27en_US
dc.identifier.wosWOS:001258543900011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherWolters Kluwer Medknow Publicationsen_US
dc.relation.ispartofNigerian Journal of Clinical Practiceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial neural networken_US
dc.subjectgender estimationen_US
dc.subjectmachine learning algorithmsen_US
dc.subjectmandibular lingulaen_US
dc.titleGender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networksen_US
dc.typeArticleen_US

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