Yusuf Secgin; Halil Saban Erkartal; Melike Tatli; Seyma Toy; Zulal Oner & Serkan Oner

The determination of sex differences in anatomical structures is critical in establishing gold standard morphometric data in basic medical sciences, and in surgical and internal sciences in selecting the right area during invasive intervention and applying the correct intervention methodology appropriate to the area. The aim of this study is to determine the sex difference using Machine learning (ML) algorithms and Artificial neural networks (ANN) with parameters obtained from basilar artery. The study was performed on computed tomography angiography images of 63 women and 94 men. The following parameters were measured on the images: initial width of the right vertebral artery, initial width of the left vertebral artery, termination width of the right vertebral artery, termination width of the left vertebral artery, basilar artery width, and basilar artery length. The measurements were used in ML algorithms and ANN input to determine sex differences. As a result of the study, a sex difference rate of 0.84 was determined with the ML algorithms Random Forest (RF), Quadratic Discriminant Analysis (QDA), Extra Tree Classifier (ETC) and 0.84 with the Multilayer Perceptron Classifier (MLCP) algorithm of ANN. As a result of the study, sex difference was found with an accuracy rate of 0.84 using ML algorithms and ANN with parameters obtained from basilar artery. In this context, we think that this study will shed light on basic and clinical medical sciences.

 KEY WORDS: Basilar artery; Machine learning algorithms; Artificial neural networks; Sex difference.

SECGIN, Y.; ERKARTAL, H. S.; TATLI, M.; TOY, S.; ONER, Z. & ONER, S. Determination of sex differences using machine learning algorithms and artificial neural networks with parameters obtained from basilar artery. Int. J. Morphol., 42(5):1295-1300, 2024.