Assessing the Greater Sciatic Notch With 2-D Shape Analysis for Sex Estimation

Journal of Archaeological Science, 2008

In this paper, three approaches for developing sample-specific sex determination methods of immature skeletal remains based on permanent tooth dimensions are proposed and tested using a sample of identified skeletons. The sample comprises adult and subadult individuals selected from the Lisbon documented skeletal collection, housed at the National Museum of Natural History in Lisbon, Portugal. Faciolingual and mesiodistal diameters were the tooth dimensions utilized. In the first approach, sex-specific logistic regression formulae based on adult tooth dimensions are developed and then used to determine the sex of the subadult sample. The second and third approaches are based on the sectioning point procedure, which uses the overall mean of a measurement (tooth diameter) collected from the sample as the discriminant criteria for determining the sex of the individuals in that sample. While in the second approach the adult overall mean of each dimension is used as the discriminant criteria for determining the sex of the subadults, in the third approach it is the subadult overall mean of each dimension that comprises the discriminant criteria that is applied back to the subadults for determining sex. Results show that the canines are the teeth with the highest sexual dimorphism and methods of sex determination based on canine dimensions provide correct allocation accuracies between 58.8% and 100% depending on the diameter and the approach that is being used. Canine faciolingual dimensions provide the best overall results. Combinations of measurements from the same and different teeth do not increase significantly the accuracy of the methods and approaches. Some of the problems of subadult sex determination methods based on adult tooth dimensions result from differing levels of sexual dimorphism between the adult and subadult segment of the sample. Mortality or cultural bias may increase or decrease the sexual dimorphism of the subadults compared to the adults. Small subadult samples utilized in this study may also raise questions regarding the accuracy of the three different samplespecific approaches. However, high consistency of results using the canine and different approaches, suggests that adult and subadult canine dimensions can be reliable sex discriminators of immature skeletal remains in archaeological samples. The major advantage of the approaches presented here is that they can be used to derive sample-specific methods and, therefore, eliminate the problem of applying morphological or metric methods to individuals originating from a population that differs from the one that contributed to the development of the method.

JOURNAL OF BIOENGINEERING OF AND TECCHNOLOGY applied to Health, 2019

There are several methods used in the identification process of human remains. The most of them are based on comparing of antemortem and postmortem data available. Although the technique of fingerprinting is considered more accurate in many cases, it cannot be used when the bodies are mutilated, decomposed, burned, or fragmented. This article aims to compare the metric values obtained by Galvão (1994) and Saliba (2001) to differentiate male and female through dry skulls, using the measurement of the Radiocef Studio 2 Program. It was used 16 teleradiographs (11 females and 5 males). The linear measurements used in this article were: 1. The bodies stature of the mandible; and 2. Distance Nasium-Front Nasal Spine. Several radiological techniques are used to aid the human identification process for determining sex, ethnic group, and age. The analyses of X-rays and Computer Tomography (CT) scans, antemortem and postmortem, have been an important tool for human identification in forensic dentistry, especially with the refinement of techniques acquired with the advancement of radiology and CT scans. We concluded that the knowledge of the best method by forensic dentists with a careful application of the technique and report's interpretation is essential to fulfilling the necessary characteristics for a successful identification of sex using skull measures.

La Revue de Médecine Légale, 2017

Journal of forensic sciences, 2010

Three studies have proposed discriminant functions for sex determination from deciduous tooth crown dimensions, and this study tests the existing functions on a sample of 46 Portuguese immature skeletons of known sex, aged from birth to 10 years. Deciduous teeth were measured in their mesiodistal and faciolingual crown dimensions, and percentage of correct allocation accuracy in determining sex using each specific function was determined. Discriminant functions were also calculated from data collected for this study and tested using cross-validation. Results show poor overall accuracy (33.3-75%) and poor cross-validation (46.2-60.0%). This is related to low sexual dimorphism in deciduous tooth crown size, as well as differences in degree of sexual dimorphism and in overall tooth size between different samples. For these reasons, deciduous crown size does not seem to show significant forensic value as discriminator of sex, particularly when methods developed on one population are applied to individuals of another population.

Legal Medicine, 2020

The classification performance of the statistical methods binary logistic regression (BLR), multinomial and penalized multinomial logistic regression (MLR, pMLR), linear discriminant analysis (LDA), and the machine learning algorithms naïve Bayes classification (NBC), decision trees (DT), random forest (RF), artificial neural networks (ANN), support vector machines (linear, polynomial or radial) (SVM), multivariate adaptive regression splines (MARS), and extreme gradient boosting (XGB) is examined in skeletal sex/ancestry estimation. The datasets used to test the performance of these methods were obtained from a documented human skeletal collection , Athens Collection, and the Howells Craniometric data set. For their implementation, an R package has been written to search for the optimum tuning parameters under cross-validation and perform sex/ancestry classification. It was found that the classification performance may vary significantly depending on the problem. From the methods tested, LDA and the machine learning technique of linear SVM exhibit the best performance, with high prediction accuracy and relatively low bias in most of the tests. ANN and pMLR can generally be considered to give satisfactory predictions, whereas NBC when using metric traits and DT are the worst of the classification methods examined. The possibility of making the models developed via the machine learning algorithms applicable to other assemblages without the use of a training sample is also discussed.

Journal of Forensic …, 2011

Identifying group affinity from human crania is a long-standing problem in forensic and physical anthropology. Many craniofacial differences used in forensic skeletal identification are difficult to quantify, although certain measurements of the midfacial skeleton have shown high predictive value for group classifications. This study presents a new method for analyzing midfacial shape variation between different geographic groups. Three-dimensional laser scan models of 90 crania from three populations were used to obtain cross-sectional midfacial contours defined by three standard craniometric landmarks. Elliptic Fourier transforms of the contours were used to extract Fourier coefficients for statistical analysis. After cross-validation, discriminant functions based on the Fourier coefficients provided an average of 86% correct classifications for crania from the three groups. The high rate of accuracy of this method indicates its usefulness for identifying group affinities among human skeletal remains and demonstrates the advantages of digital 3D model-based analysis in forensic research.

2020

ABSTRACTObjectivesUsing cranial measurements in two Italian populations, we compare machine learning methods to the more traditional method of linear discriminant analysis in estimating sex. We use crania in sex estimation because it is useful especially when remains are fragmented or displaced, and the cranium may be the only remains found.Materials and MethodsUsing the machine learning methods of decision tree learning, support-vector machines, k-nearest neighbor algorithm, and ensemble methods we estimate the sex of two populations: Samples from Bologna and samples from the island of Sardinia. We used two datasets, one containing 17 cranial measurements, and one measuring the foramen magnum.Results and DiscussionOur results indicate that machine learning models produce similar results to linear discriminant analysis, but in some cases machine learning produces more consistent accuracy between the sexes. Our study shows that sex can be accurately predicted (> 80%) in Italian po...