Articlediamond2023

Gender Estimation with Parameters Obtained From the Upper Dental Arcade by Using Machine Learning Algorithms and Artificial Neural Networks

Halil Şaban Erkartal · Melike Tatlı · Yusuf Seçgin · Şeyma Toy · Şuayip Burak Duman

10 citations0/0 files storedEuropean Journal of Therapeutics

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Forensic Anthropology and Bioarchaeology Studies Orthodontics and Dentofacial Orthopedics Dental Radiography and Imaging

Abstract

Objective: The aim of this study is to estimate gender with parameters obtained from the upper dental arcade by using machine learning algorithms and artificial neural networks. Methods: The study was conducted on cone-beamed computed tomography images of 176 individuals between the ages of 18 and 55 who did not have any pathologies or surgical interventions in their upper dental arcade. The images obtained were transferred to RadiAnt DICOM Viewer program in Digital Imaging and Communications in Medicine format and all images were brought to orthogonal plane by applying 3D Curved Multiplanar Reconstruction. Length and curvature length measurements were performed on these images brought to orthogonal plane. The data obtained were used in machine learning algorithms (ML) and artificial neural networks input and rates of gender estimation were shown. Results: In the study, an accuracy ratio of 0.86 was found with ML models linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR) algorithm and an accuracy ratio of 0.86 was found with random forest (RF) algorithm. It was found with SHAP analyser of RF algorithm that the parameter of width at the level of 3rd molar teeth contributed the most to gender. An accuracy rate of 0.92 was found as a result of training for 500 times with multilayer perceptron classifier (MLCP), which is an artificial neural network (ANN) model. Conclusion: As a result of our study, it was found that the parameters obtained from the upper dental arcade showed a high accuracy in estimation of gender. In this context, we believe that the present study will make important contributions to forensic sciences.

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References

1963The human skeleton in forensic medicine 2006Sex Determination Using Nonmetric Characteristics of the Mandible in Koreans*1976Physical variation and history in Melanesia and Australia 1996A cross-sectional study of canine dimorphism in establishing sex identity: comparison of two statistical methods 2019Sex estimation using sternum part lenghts by means of artificial neural networks 2022Machine Learning Techniques for Human Age and Gender Identification Based on Teeth X-Ray Images 2019A trial on artificial neural networks in predicting sex through bone length measurements on the first and fifth phalanges and metatarsals 2021Gender prediction with parameters obtained from pelvis computed tomography images and decision tree algorithm

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