Data mining for sex estimation based on cranial measurements.

The aim of the present study is to develop effective and understandable classification models for sex estimation and to identify the most dimorphic linear measurements in adult crania by means of data mining techniques. Furthermore, machine learning models and models developed through logistic regression analysis are compared in terms of performance. Computed tomography scans of 393 adult individuals were used in the study. A landmark-based approach was applied to collect the metric data. The three-dimensional coordinates of 47 landmarks were acquired and used for calculation of linear measurements. Two datasets of cranial measurements were assembled, including 37standard measurements and 1081 interlandmark distances, respectively. Three data mining algorithms were applied: the rule induction algorithms JRIP and Ridor, and the decision tree algorithm J48. Two advanced attribute selection methods (Weka BestFirst and Weka GeneticSearch) were also used. The best accuracy result (91.9 %) was achieved by a set of rules learnt by the JRIP algorithm from the dataset constructed by application of the GeneticSearch selection algorithm to the dataset of standard cranial measurements. The set consisted of five rules including seven cranial measurements. Its accuracy was even better than the classification rates achieved by the logistic regression models. Concerning the second dataset of nonstandard measurements, the best accuracy (88.3 %) was obtained by using classification models learnt by two algorithms - JRIP with a dataset preprocessed by the BestFirst selection algorithm and Ridor with preprocessing by the GeneticSearch selection algorithm. Our experiments show that for the two datasets mentioned above the rule-based models contain smaller sets of rules with shorter lists of measurements and achieve better classification accuracy results in comparison with decision tree-based models.

Sex estimation by Mastoid Triangle using 3D models.

Mastoid Triangle (MT) is a triangle constructed between the landmarks porion, mastoidale and asterion. The aim of the study is to evaluate the sex differences in the MT size in Bulgarian adults and to develop discriminant functions for sex estimation based on the MT sides and area. The study was carried out on 148 head CT scans. A sample of 53 males and 53 females was used for development of discriminant functions, and a test sample of 21 males and 21 females was applied for their validation. Using the software InVesalius©, 3D models of the skulls were segmented and exported in STL format. The 3D coordinates of the landmarks porion, asterion and mastoidale were collected using the software MeshLab©. The MT sides, area and angles were calculated. The sex differences were assessed by the independent t-test. Bilateral differences were evaluated using the paired t-test. Univariate and multivariate discriminant function analyses were applied. The results showed that the MT sides and area differed significantly between both sexes. Sex differences were also established for the angle at mastoidale. Bilateral differences were found in males for the distance porion-mastoidale, which was significantly greater on the right side. The MT dimensions showed sufficient discriminating power for sex estimation among Bulgarians (up to 89%), and the total MT area proved to be the best single sex discriminating trait. The test sample corroborated the usefulness of the MT in sex estimation demonstrating similar or higher overall accuracy rates.