Sex estimation from the hyoid bone measurements in an adult Eastern Turkish population using 3D CT images, discriminant function analysis, support vector machines, and artificial neural networks☆

Demet MUTLU G., ASIRDIZER M., Kartal E., Keskin S., MUTLU İ., Göya C.

Legal Medicine, cilt.67, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 67
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.legalmed.2023.102383
  • Dergi Adı: Legal Medicine
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CINAHL, Criminal Justice Abstracts, MEDLINE
  • Anahtar Kelimeler: Artificial Neural Networks, Discriminant Function Analysis, Hyoid Bone, Sex Estimation, Support Machine Vectors
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

The hyoid bone is one of the bones in the human body that shows sexual dimorphism. The anthropological and anthropometric characteristics that determine sexual dimorphism are influenced by demographic differences. The aim of this study was to investigate the rate of sexual dimorphism of the hyoid bone in the adult Eastern Turkish population from the examination of the 3D computed tomography images of 240 patients, using discriminant function analysis (DFA), support vector machines (SVM), and artificial neural networks (ANN). These evaluations were based on eight hyoid measurements that have been frequently used in previous CT studies. The results showed that all eight measurements were higher in males than in females (p = 0.000). It was determined that sex could be estimated accurately at up to 93.3 % using DFA, 93.8 % using SVM and 95.4 % using ANN. The maximum accuracy rate achieved to 94.2 % in males using SVM, and 95.8 % in females using ANN. These high rates of sexual dimorphism found using DFA, SVM, and ANN in this study indicate that characteristics of the hyoid bone can be utilized to determine sex in the Eastern Turkish population.