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The construction of a complete biological profile for unknown individuals from skeletal remains plays a key role in the holistic study of archaeological sites. However, the presence of commingled elements, as in the case of mass graves, hinders this process. This work aims to evaluate the diaphyseal cross‐sectional geometric properties of the long bones for pair‐matching and for sex estimation based on the femur, tibia, and humerus bones on archaeological and historical samples. The sample consisted of 3D virtual bone models of 95 individuals (46 males, 39 females, 10 of unknown sex) from both Greek and English assemblages, utilizing the dedicated "csg‐toolkit" GNU Octave package for variable extraction. The pair‐matching sorting algorithm performed adequately in all three assemblages, excluding over 97% of the true mismatched pairs. The accuracy rate for certain pair detection was close to 50% for the lower limbs, and 41% for the humerus, with the algorithm deeming a significant amount of the missed pairs as plausible, resulting in 70% to 80% of total pairs to be detected in some capacity for all bone assemblages. The sex estimation classifiers performed sufficiently in all cases, yielding moderately high accuracy rates in the majority of examined samples, with values consistently higher than 70%. However, the application of contemporary methods on archaeological or historical material needs to be performed with caution, as secular changes and population‐specific trends can affect the applicability of the methods. As such, the utilization of different techniques before reaching a conclusion is vital and should be encouraged. [ABSTRACT FROM AUTHOR]

Despite developing prior to the appearance of secondary sexual characteristics of the skeleton, the permanent dentition exhibits sexual dimorphism. Therefore, teeth can serve as a means to estimate sex assigned at birth even in young individuals. This project takes a large global sample of maximum dimensions of the crown as well as measurements of the crown at the cervix to explore sexual dimorphism. Dimorphism is noted in teeth throughout the dental arcade, particularly in the canines. We provide sectioning points as well as the probability of correct classification (ranging from 50.9% to 81.3%) for each measurement to aid the practitioner in sex estimation from the dentition. This research provides a method to estimate sex without arbitrary population specifications. We argue for a global approach that incorporates more population variation to remove the need to estimate "ancestry," (which in actuality is translated to a social race category) and therefore does not force sexual dimorphism‐related variation into these mutable and ambiguous categories. Further, this paper demonstrates the utility of the dentition as an additional indicator to aid with the estimation of sex assigned at birth in forensic anthropology. The goal of this research is to better understand the expression of sexual dimorphism across the skeleton in a global context. [ABSTRACT FROM AUTHOR]

Estimating biological sex is a crucial aspect of forensic anthropology, and is pivotal in forensic investigations. Presently, the most frequently adopted osteological sex estimation methods focus on the anterior pelvis, which is easily susceptible to postmortem damage, revealing a need for additional accurate methods. This study introduces a novel method for estimating adult sex through metric pelvic scar analysis, using a known skeletal sample (169 females; 51 males). Relationships between sex and scar dimensions were subjected to Kendall's tau‐B testing, and the strongest associated measurements were further analyzed using binary logistic regression to determine their predictive capacity. The final estimation method was tested on an additional known‐sex sample of 43 males and 43 females from the Spitalfields skeletal collection. All associations between biological sex and scar measurements were significant, with the preauricular sulcus and newly defined inferior interosseous cavity presenting the strongest relationships (τb 0.223–0.504). Individual regression models using the approximate volume of each feature predicted sex with over 80% accuracy, but when combined in a single regression model, the accuracy increased to an impressive 97.1%. When then applied to the validation sample, the final estimation model achieved an accuracy of 90.7%. These results highlight the high estimation accuracy achieved by simultaneously utilizing the approximate volume of the sulcus and the inferior cavity. This is not only highly accurate but also utilizes the sturdier posterior pelvis, making it a promising tool for forensic investigations and the wider field of osteology. [ABSTRACT FROM AUTHOR]

Thanks to technical progress and the availability of virtual data, sex estimation methods as part of a biological profile are undergoing an inevitable evolution. Further reductions in subjectivity, but potentially also in measurement errors, can be brought by approaches that automate the extraction of variables. Such automatization also significantly accelerates and facilitates the specialist's work. The aim of this study is (1) to apply a previously proposed algorithm (Kuchař et al. 2021) to automatically extract 10 variables used for the DSP2 sex estimation method, and (2) to test the robustness of the new automatic approach in a current heterogeneous population. For the first aim, we used a sample of 240 3D scans of pelvic bones from the same individuals, which were measured manually for the DSP database. For the second aim a sample of 108 pelvic bones from the New Mexico Decedent Image Database was used. The results showed high agreement between automatic and manual measurements with rTEM below 5% for all dimensions except two. The accuracy of final sex estimates based on all 10 variables was excellent (error rate 0.3%). However, we observed a higher number of undetermined individuals in the Portuguese sample (25% of males) and the New Mexican sample (36.5% of females). In conclusion, the procedure for automatic dimension extraction was successfully applied both to a different type of data and to a heterogeneous population. [ABSTRACT FROM AUTHOR]

Continual re-evaluation of standards for forensic anthropological analyses are necessary, particularly as new methods are explored or as populations change. Indian South Africans are not a new addition to the South African population; however, a paucity of skeletal material is available for analysis from medical school collections, which has resulted in a lack of information on the sexual dimorphism in the crania. For comparable data, computed tomography scans of modern Black, Coloured and White South Africans were included in addition to Indian South Africans. Four cranial morphoscopic traits, were assessed on 408 modern South Africans (equal sex and population distribution). Frequencies, Chi-squared tests, binary logistic regression and random forest modelling were used to assess the data. Males were more robust than females for all populations, while White South African males were the most robust, and Black South African females were the most gracile. Population differences were noted among most groups for at least two variables, necessitating the creation of populations-specific binary logistic regression equations. Only White and Coloured South Africans were not significantly different. Indian South Africans obtained the highest correct classifications for binary logistic regression (94.1%) and random forest modelling (95.7%) and Coloured South Africans had the lowest correct classifications (88.8% and 88.0%, respectively). This study provides a description of the patterns of sexual dimorphism in four cranial morphoscopic traits in the current South African population, as well as binary logistic regression functions for sex estimation of Black, Coloured, Indian and White South Africans. [ABSTRACT FROM AUTHOR]

Klales et al. (2012) is a popular standard for the estimation of skeletal sex. Since its publication, a number of studies have demonstrated that population-specific applications of Klales improve classification accuracy. However, it has also been shown that age appears to affect the expression of dimorphism in the pelvis across the lifespan. As such, the present study examines the accuracy of Klales, and the modified global standard of Kenyhercz et al. (2017), in a contemporary Indonesian population, including quantifying the effect of age. Pelvic multi-slice CT scans of 378 individuals (213 female; 165 male) were analysed in OsiriX®. Both standards were tested and Indonesian-specific models thereafter derived. When applied to the Indonesian sample, both the Klales and Kenyhercz standards resulted in lower classification accuracy relative to the original studies. In considering the Indonesian-specific models, the ventral arc was the most accurate for the classification of sex, at 93.3% with a − 3.0% sex bias. The accuracy of the three-trait model was 94.4%, with a − 5.5% sex bias. Age was shown to significantly affect the distribution of pelvic trait scores. As such, age-dependent models were also derived, with the standard for individuals between 30 and 49 years the most accurate, at 93.1% and a sex bias of − 4.0%. Accuracy was lower in individuals aged ≥ 50 years, at 91.3% and a sex bias of 4.1%. These findings support the importance of establishing population-specific standards and to facilitate improved accuracy and capabilities for forensic practitioners in Indonesia. [ABSTRACT FROM AUTHOR]

Sex estimation is a critical component of the biological profile, and forensic anthropologists may use a variety of sex estimation methods depending upon the degree of completeness and state of preservation of the skeletal remains being analyzed. The innominate is widely accepted to be the most sexually dimorphic skeletal element. The Diagnose Sexuelle Probabiliste (DSP) method, which uses 10 measurements of the innominate, was introduced in 2005 and updated as DSP2 in 2017. While DSP2 has been reported to have high classification accuracy rates in studies of South American and European populations, the method has not been widely tested in US samples, and few US practitioners incorporate this method into their casework. The goal of this study was to test the reliability and accuracy of DSP2 using a large, modern sample from the US (n = 174). Two observers, blinded from demographic information associated with each specimen, collected the DSP2 metrics. Intra‐ and interobserver error analyses showed acceptable levels of agreement for all measurements, except for IIMT. Classification accuracies exceeded 95%, with minimal sex bias, for both observers and using various measurement combinations; however, an inclusivity sex bias occurred with more males reaching the 0.95 posterior probability threshold required by DSP2 to provide a sex classification estimate. Based on its high accuracy, forensic anthropologists in the US may consider incorporating DSP2 into their casework, although we recommend excluding IIMT and using SPU with caution. Additional methods will continue to be needed when the posterior probability threshold is not reached. [ABSTRACT FROM AUTHOR]

Accurate sex estimation is crucial for comprehensive analysis of the biological profiles of unidentified human skeletal remains. However, there is a notable lack of research specifically addressing the morphometrics of the hard palate. Therefore, this study aimed to derive discriminant equations using the hard palate and assess their applicability for sexing partial skeletal remains in a contemporary Korean population. Statistical analyses were performed for 24 measurements derived from three-dimensional models of the hard palate, generated using computed tomography scans of 301 individuals (156 males, 145 females). Descriptive statistics revealed significant sexual dimorphism in the mean comparison of hard palate sizes between Korean males and females, with males exhibiting larger palates across all measurements (p < 0.05). Discriminant function score equations were generated to aid in sex determination. Univariate analysis yielded an accuracy range of 57.8–75.1%, whereas the stepwise method achieved an accuracy of 80.7% with five selected variables: IF-PNS, GFL-GFR, IF-GFR, Pr-EcL, and Pr-EnR. The results of this metric analysis demonstrate the usefulness of the hard palate for sex estimation in the contemporary Korean population. These findings have potential implications for forensic investigations, archeological studies, and population-specific anatomical research. [ABSTRACT FROM AUTHOR]

The morphometric measurement of the hyoid bone has been extensively studied in the literature, although morphological evaluations are covered in a limited number of studies. The aim of this study was to ascertain the fusion status and hyoid bone type and their relationships with age groups and sex. An examination was made of computed tomography scans of 320 patients. The types and degrees of fusion of the hyoid bone were determined. Hyoid type-U was most frequently observed in males (25.6%), type-D in females (31.9%) and the overall population (30.8%). There was no statistically significant difference in fusion formation on the right and left sides. The number of bones with fusion increased in both sexes with age (p=0.001). The earliest fusion observed was in a case aged 16 years, and 50% of the cases did not have fusion at age 61 years or older. Unlike previous studies, hyoid type and fusion status were evaluated using discriminant function analysis. Hyoid type and fusion cannot be indicative criteria for sex and age determination, but it might be feasible to accurately identify a person younger than twenty years old. The data obtained in the current study can be considered to make an important contribution to future studies. [ABSTRACT FROM AUTHOR]

Simple Summary: Sex estimation based on bones is a technique used to determine the biological sex of an individual from skeletal remains. It relies on the anatomical differences between male and female skeletons. Various bone characteristics have been incorporated into methods for sex estimation. Linear measurements are commonly used features in classification models for sex estimation. On the other hand, angle measurements are rarely included in such models, although they are important characteristics of the geometry of the bones and could provide essential information for the discrimination between the male and female bones. The goal of this research is to examine the potential of cranial angles for sex estimation and to identify the set of the most dimorphic angles by applying machine learning algorithms. The development of current sexing methods largely depends on the use of adequate sources of data and adjustable classification techniques. Most sex estimation methods have been based on linear measurements, while the angles have been largely ignored, potentially leading to the loss of valuable information for sex discrimination. This study aims to evaluate the usefulness of cranial angles for sex estimation and to differentiate the most dimorphic ones by training machine learning algorithms. Computed tomography images of 154 males and 180 females were used to derive data of 36 cranial angles. The classification models were created by support vector machines, naïve Bayes, logistic regression, and the rule-induction algorithm CN2. A series of cranial angle subsets was arranged by an attribute selection scheme. The algorithms achieved the highest accuracy on subsets of cranial angles, most of which correspond to well-known features for sex discrimination. Angles characterizing the lower forehead and upper midface were included in the best-performing models of all algorithms. The accuracy results showed the considerable classification potential of the cranial angles. The study demonstrates the value of the cranial angles as sex indicators and the possibility to enhance the sex estimation accuracy by using them. [ABSTRACT FROM AUTHOR]

Abstract Cranial sex estimation often relies on visual assessments made by a forensic anthropologist following published standards. However, these methods are prone to human bias and may be less accurate when applied to populations other than those for which they were originally developed with. This study explores an automatic deep learning (DL) framework to enhance sex estimation accuracy and reduce bias. Utilising 200 cranial CT scans of Indonesian individuals, various DL network configurations were evaluated against a human observer. The most accurate DL network, which learned to estimate sex and cranial traits as an auxiliary task, achieved a classification accuracy of 97%, outperforming the human observer at 82%. Grad-CAM visualisations indicated that the DL model appears to focus on certain cranial traits, while also considering overall size and shape. This study demonstrates the potential of using DL to assist forensic anthropologists in providing more accurate and less biased estimations of skeletal sex.

Abstract Accurate sex estimation is crucial for comprehensive analysis of the biological profiles of unidentified human skeletal remains. However, there is a notable lack of research specifically addressing the morphometrics of the hard palate. Therefore, this study aimed to derive discriminant equations using the hard palate and assess their applicability for sexing partial skeletal remains in a contemporary Korean population. Statistical analyses were performed for 24 measurements derived from three-dimensional models of the hard palate, generated using computed tomography scans of 301 individuals (156 males, 145 females). Descriptive statistics revealed significant sexual dimorphism in the mean comparison of hard palate sizes between Korean males and females, with males exhibiting larger palates across all measurements (p

Abstract Prompt personal identification is required during disasters that can result in many casualties. To rapidly estimate sex based on skull structure, this study applied deep learning using two-dimensional silhouette images, obtained from head postmortem computed tomography (PMCT), to enhance the outline shape of the skull. We investigated the process of sex estimation using silhouette images viewed from different angles and majority votes. A total of 264 PMCT cases (132 cases for each sex) were used for transfer learning with two deep-learning models (AlexNet and VGG16). VGG16 exhibited the highest accuracy (89.8%) for lateral projections. The accuracy improved to 91.7% when implementing a majority vote based on the results of multiple projection angles. Moreover, silhouette images can be obtained from simple and popular X-ray imaging in addition to PMCT. Thus, this study demonstrated the feasibility of sex estimation by combining silhouette images with deep learning. The results implied that X-ray images can be used for personal identification.

Abstract Background Identification is one of the main aspects of forensics. Sex estimation is an essential part of identification because it can simplify the whole process. Mandible is the largest, strongest, and sexually dimorphic bone and is part of the orofacial structure, which has the second highest level of dimorphism after the pelvic bone. Sex estimation using the mandible can be performed by conducting various linear measurements on a panoramic radiograph, including right minimum ramus width (RMiRW), left minimum ramus width (LMiRW), right projective height of ramus (RPHR), left projective height of ramus (LPHR), right maximum ramus width (RMxRW), left maximum ramus width (LMxRW), right coronoid height (RCH), left coronoid height (LCH), symphysis height (SH), right mandibular corpus height (RMCH), and left mandibular corpus height (LMCH). This study aimed to analyze how linear measurements in panoramic radiographs differ between men and women and to estimate sex by utilizing these parameters. Results In this study, 195 panoramic radiographs from 95 men and 100 women aged 20–40 years obtained from our dental hospital were used as a training data. Meanwhile, 61 panoramic radiographs from 29 men and 32 women outside the training data with same characteristics were used as the testing data. The linear measurements of the mandible using panoramic radiographs were taken with EzDent-i Vatech software. Independent t-test showed significant difference (p < 0.05) in some linear measurements of the mandible between adult men and women. These significantly different linear measurements were then subjected to discriminant function analysis to produce sex estimation equations. The equation accuracy percentage ranged between 63.6 and 94.4% for the training sample and 59.5% and 85% for the testing sample. Conclusion The linear measurements of the mandible using diagnostically acceptable panoramic radiographs taken from a patient with standardized head positioning can serve as an alternative method for sex estimation. The accuracy of discriminant analysis for sex estimation varies depending on the parameter used in the estimation.

Abstract Background The identification of skeletal remains begins with a sex evaluation since other biological profile elements, such as size and age, are sex-specific. The pelvis is the favored element for sex assessment since it is very sexually dimorphic. Aim of the study Delivering hand and foot bones sex estimate criteria for Egyptian population identification was the goal of this work. Subject and methods Eighty-two Egyptian adult subjects (41 males and 41 females) aged ≥ 21 years old were subjected to MRI scan on the right hand and foot to assess 9 measurements: hand length, hand width, four measurements of middle metacarpal bone (length, breadth, head breadth and base breadth), first metatarsal bone length, first metatarsal bone width and (first metatarsal bone length x first metatarsal bone width). Results All the measured parameters in the right hand and foot were higher in males than females. First metatarsal bone length x first metatarsal bone width in the foot and middle metacarpal bone breadth in the hand were the most sexually dimorphic parameters, with accuracy of 86.6 percent and 84.1 percent, respectively. In stepwise discriminant analysis, three of nine measurements were selected: First metatarsal bone length x first metatarsal bone width, middle metacarpal bone breadth and hand width for the sex prediction equation in the Egyptian population, with a cross-validated sex classification accuracy of 90.2%. Conclusion Sex can be assessed from hand and foot metric parameters measured by MRI with high accuracy.

Abstract Background Forensic anthropological examinations help in identification of unidentified human remains. This study aims to establish population-specific standards for age estimation from the sternal ends of left fourth ribs in the Nepalese population. A quantitative, observational study was conducted on 387 Nepalese deceased (106 females, 281 males) between November 2021 and March 2023. Left fourth ribs were collected, macerated and examined for the study. The variables examined included pit depth, pit shape, rim and wall configurations and rib phase. Results Pit depth significantly predicted age, β = 0.642, t(385) = 16.42, p

Prompt personal identification is required during disasters that can result in many casualties. To rapidly estimate sex based on skull structure, this study applied deep learning using two-dimensional silhouette images, obtained from head postmortem computed tomography (PMCT), to enhance the outline shape of the skull. We investigated the process of sex estimation using silhouette images viewed from different angles and majority votes. A total of 264 PMCT cases (132 cases for each sex) were used for transfer learning with two deep-learning models (AlexNet and VGG16). VGG16 exhibited the highest accuracy (89.8%) for lateral projections. The accuracy improved to 91.7% when implementing a majority vote based on the results of multiple projection angles. Moreover, silhouette images can be obtained from simple and popular X-ray imaging in addition to PMCT. Thus, this study demonstrated the feasibility of sex estimation by combining silhouette images with deep learning. The results implied that X-ray images can be used for personal identification. [ABSTRACT FROM AUTHOR]

Background: Identification is one of the main aspects of forensics. Sex estimation is an essential part of identification because it can simplify the whole process. Mandible is the largest, strongest, and sexually dimorphic bone and is part of the orofacial structure, which has the second highest level of dimorphism after the pelvic bone. Sex estimation using the mandible can be performed by conducting various linear measurements on a panoramic radiograph, including right minimum ramus width (RMiRW), left minimum ramus width (LMiRW), right projective height of ramus (RPHR), left projective height of ramus (LPHR), right maximum ramus width (RMxRW), left maximum ramus width (LMxRW), right coronoid height (RCH), left coronoid height (LCH), symphysis height (SH), right mandibular corpus height (RMCH), and left mandibular corpus height (LMCH). This study aimed to analyze how linear measurements in panoramic radiographs differ between men and women and to estimate sex by utilizing these parameters. Results: In this study, 195 panoramic radiographs from 95 men and 100 women aged 20–40 years obtained from our dental hospital were used as a training data. Meanwhile, 61 panoramic radiographs from 29 men and 32 women outside the training data with same characteristics were used as the testing data. The linear measurements of the mandible using panoramic radiographs were taken with EzDent-i Vatech software. Independent t-test showed significant difference (p < 0.05) in some linear measurements of the mandible between adult men and women. These significantly different linear measurements were then subjected to discriminant function analysis to produce sex estimation equations. The equation accuracy percentage ranged between 63.6 and 94.4% for the training sample and 59.5% and 85% for the testing sample. Conclusion: The linear measurements of the mandible using diagnostically acceptable panoramic radiographs taken from a patient with standardized head positioning can serve as an alternative method for sex estimation. The accuracy of discriminant analysis for sex estimation varies depending on the parameter used in the estimation. [ABSTRACT FROM AUTHOR]

Background & objective: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements. Material & methods: In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5–17 years; 162 males and 159 females, aged 18–72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt. Results: Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18–27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age. Conclusion: The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable. [ABSTRACT FROM AUTHOR]

Chile had a violent military coup (1973–1990) that resulted in 3,000 victims declared detained, missing or killed; many are still missing and unidentified. Currently, the Human Rights Unit of the Forensic Medical Service in Chile applies globally recognised forensic anthropological approaches, but many of these methods have not been validated in a Chilean sample. As current research has demonstrated population-specificity with extant methods, the present study aims to validate sex estimation methods in a Chilean population and thereafter establish population-specific equations. A sample of 265 os coxae of known age and sex of adult Chileans from the Santiago Subactual Osteology Collection were analysed. Visual assessment and scoring of the pelvic traits were performed in accordance with the Phenice (1969) and Klales et al. (2012) methods. The accuracy of Phenice (1969) in the Chilean sample was 96.98%, with a sex bias of 7.68%. Klales et al. (2012) achieved 87.17% accuracy with a sex bias of -15.39%. Although both methods showed acceptable classification accuracy, the associated sex bias values are unacceptable in forensic practice. Therefore, six univariate and eight multivariate predictive models were formulated for the Chilean population. The most accurate univariate model was the ventral arc at 96.6%, with a sex bias of 5.2%. Classification accuracy using all traits was 97.0%, with a sex bias of 7.7%. This study provides Chilean practitioners a population-specific morphoscopic standard with associated classification probabilities acceptable to accomplish legal admissibility requirements in human rights and criminal cases specific to the second half of the 20th century. [ABSTRACT FROM AUTHOR]

In this study we tested classification performance of a sex estimation method from the mandible originally developed by Sella-Tunis et al. (2017) on a heterogeneous Israeli population. Mandibular linear dimensions were measured on 60 CT scans derived from the Czech living population. Classification performance of Israeli discriminant functions (DFs-IL) was analyzed in comparison with calculated Czech discriminant functions (DFs-CZ) while different posterior probability thresholds (currently discussed in the forensic literature) were employed. Our results comprehensively illustrate sensitivity of different discriminant functions to population differences in body size and degree of sexual dimorphism. We demonstrate that the error rate may be biased when presented per posterior probability threshold. DF-IL 1 showed least sensitivity to population origin and fulfilled criteria of sufficient classification performance when applied on the Czech sample with a minimum posterior probability threshold of 0.88 reaching overall accuracy ≥ 95%, zero sex bias, and 80% of classified individuals. The last parameter was higher in DF-CZ 1 which was the main difference between those two DFs suggesting relatively low dependance on population origin. As the use of population-specific methods is often prevented by complicated assessment of population origin, DF-IL 1 is a candidate for a sufficiently robust method that could be reliably applied outside the reference sample, and thus, its classification performance deserves further testing on more population samples. [ABSTRACT FROM AUTHOR]

The development of sex estimation standards, especially in locations with high murder case loads like South Africa, is important to aid in establishing the biological profile of victims. There is a lack of information on the utility of the measurements around the metatarsal diaphyseal nutrient foramina (NF) in sex estimation in South Africans of Mixed ancestry (SAMA). Five measurements around the NF were taken from a total of 248 metatarsals (first to fifth) from 28 males and 23 females of SAMA population. Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included total length, distance from proximal end to NF, circumference, and mediolateral and dorsoplantar diameters at the level of the NF. The univariable functions produced 60.8–80% accuracy rates. The original classification accuracies for the stepwise and direct DFA multivariable functions ranged from 75.5–80% and 75–81.3%, respectively. The original classification accuracies for the stepwise and direct LRA multivariable functions ranged from 75.5%–80% and 75%–83.7%, respectively. The cross-validation classifications showed a drop of 0–4% for DFA and 0.7–5.4% for LRA. The multivariable DFA and LRA functions produced high average classification accuracies appropriate for use in forensic settings. [ABSTRACT FROM AUTHOR]

Background: Forensic anthropological examinations help in identification of unidentified human remains. This study aims to establish population-specific standards for age estimation from the sternal ends of left fourth ribs in the Nepalese population. A quantitative, observational study was conducted on 387 Nepalese deceased (106 females, 281 males) between November 2021 and March 2023. Left fourth ribs were collected, macerated and examined for the study. The variables examined included pit depth, pit shape, rim and wall configurations and rib phase. Results: Pit depth significantly predicted age, β = 0.642, t(385) = 16.42, p < 0.001. Pit depth also explained a significant proportion of variance in age, R2 = 0.41, F(1, 385) = 269.54, p < 0.001. The age estimates from pit depth stage were 7–36 (stage 0), 7–49 (stage 1), 16–51 (stage 2), 10–58 (stage 3), 22–70 (stage 4) and 32–81 (stage 5). Age estimates for pit shape were 17–20 (stage 0), 13–48 (stage 2), 15–55 (stage 3), 24–68 (stage 4) and 39–82 (stage 5). Age estimates for rim and wall configurations were 17–20 (stage 0), 13–47 (stage 2), 17–53 (stage 3), 24–68 (stage 4) and 40–82 (stage 5). Similarly, age estimates for rib phase were 17–20 (phase 0), 18–20 (phase 1), 13–46 (phase 2), 18–50 (phase 3), 23–60 (phase 4), 32–71 (phase 5), 50–76 (phase 6), 44–81 (phase 7) and 62–85 (phase 8). The study also examined the use of transitional analysis to develop posterior probability distributions for estimation of age using rib phases. Conclusion: This study found significant differences in the age estimates from previous studies and shows the importance of developing population-specific models for use in forensic anthropology. [ABSTRACT FROM AUTHOR]

Background: The identification of skeletal remains begins with a sex evaluation since other biological profile elements, such as size and age, are sex-specific. The pelvis is the favored element for sex assessment since it is very sexually dimorphic. Aim of the study: Delivering hand and foot bones sex estimate criteria for Egyptian population identification was the goal of this work. Subject and methods: Eighty-two Egyptian adult subjects (41 males and 41 females) aged ≥ 21 years old were subjected to MRI scan on the right hand and foot to assess 9 measurements: hand length, hand width, four measurements of middle metacarpal bone (length, breadth, head breadth and base breadth), first metatarsal bone length, first metatarsal bone width and (first metatarsal bone length x first metatarsal bone width). Results: All the measured parameters in the right hand and foot were higher in males than females. First metatarsal bone length x first metatarsal bone width in the foot and middle metacarpal bone breadth in the hand were the most sexually dimorphic parameters, with accuracy of 86.6 percent and 84.1 percent, respectively. In stepwise discriminant analysis, three of nine measurements were selected: First metatarsal bone length x first metatarsal bone width, middle metacarpal bone breadth and hand width for the sex prediction equation in the Egyptian population, with a cross-validated sex classification accuracy of 90.2%. Conclusion: Sex can be assessed from hand and foot metric parameters measured by MRI with high accuracy. [ABSTRACT FROM AUTHOR]

The development and identification of methods for effective sex estimation of physiologically juvenile remains continue to challenge bioarchaeologists. This systematic review and meta‐analysis of investigates the diagnostic accuracy of auricular surface elevation (ASE) for sex estimation of physiological juveniles; determines how the diagnostic accuracy differs between the categorical ASE method and the adapted ranked ASE method; and assesses if the diagnostic accuracy of ASE sex estimation improves with age. ASE sex estimation is used as a component of puberty estimation. A forward search using Google Scholar, SCOPUS, and CrossRef identified 248 unique documents that cited Weaver's original description of the method. The results of more than 700 sex estimates from five peer‐reviewed articles and two PhD dissertations are synthesized through bivariate meta‐analysis. The bivariate meta‐analysis reveals that ASE sex estimation correctly estimates sex of 36.7% [95% CI: 20.8–56.1%] of females and 82.4% [71.9–89.6%] of males. The predictive value of the female auricular surface trait (elevated) is 67.6% [61.8–72.9%], and the predictive value of the male trait (non‐elevated) is 56.6% [54.3–58.8%]. When separated into age cohorts of under 1 year old, under 10 years old, and over 10 years old, ASE sex estimation did not show improvement with increased age. This analysis demonstrates that the ASE sex estimation method does not accurately estimate or predict sex of physiologically juvenile individuals, with no improvement from a ranked method or by age. Furthermore, this method should not be used as a component of puberty estimation due to lack of improvement with increasing age‐at‐death. [ABSTRACT FROM AUTHOR]

An increasing number of software tools can be used in forensic anthropology to estimate a biological profile, but further studies in other populations are required for more robust validation. The present study aimed to evaluate the validity of MorphoPASSE software for sex estimation from sexually dimorphic cranial traits recorded on 3D CT models (n = 180) from three populations samples (Czech, French, and Egyptian). Two independent observers performed scoring of 4 cranial traits (2 of them bilateral) in each population sample of 30 males and 30 females. The accuracy of sex estimation using traditional posterior probability threshold (pp = 0.5) ranged from 85.6% to 88.3% and overall classification error from 14.4% to 11.7% for both observers, and corresponds to the previously published values of the method. The MorphoPASSE method is also affected by the subjectivity of the observers, as both observers show agreement in sex assignment in 83.9% of cases, regardless of the accuracy of the estimates. Applying a higher posterior probability threshold (pp 0.95) provided classification accuracy of 97.9% and 93.3% of individuals (for observer A and B respectively), minimizing the risk of error to 2.1% and 6.7%, respectively. However, sex estimation can only be applied to 54% and 66% of individuals, respectively. Our results demonstrate the validity of the MorphoPASSE software for cranial sex estimation outside the reference population. However, the achieved classification success is accompanied by a high risk of errors, the reduction of which is only possible by increasing the posterior probability threshold. [ABSTRACT FROM AUTHOR]

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and error-prone. The purpose of this study was to estimate sex and chronological age from panoramic radiographs automatically and robustly using a multi-task deep learning network (ForensicNet). ForensicNet consists of a backbone and both sex and age attention branches to learn anatomical context features of sex and chronological age from panoramic radiographs and enables the multi-task estimation of sex and chronological age in an end-to-end manner. To mitigate bias in the data distribution, our dataset was built using 13,200 images with 100 images for each sex and age range of 15–80 years. The ForensicNet with EfficientNet-B3 exhibited superior estimation performance with mean absolute errors of 2.93 ± 2.61 years and a coefficient of determination of 0.957 for chronological age, and achieved accuracy, specificity, and sensitivity values of 0.992, 0.993, and 0.990, respectively, for sex prediction. The network demonstrated that the proposed sex and age attention branches with a convolutional block attention module significantly improved the estimation performance for both sex and chronological age from panoramic radiographs of elderly patients. Consequently, we expect that ForensicNet will contribute to the automatic and accurate estimation of both sex and chronological age from panoramic radiographs. [ABSTRACT FROM AUTHOR]

There is renewed interest in Asia for the development of forensic anthropological standards, partly due to the need for population-specific models to maintain high classification accuracies. At present, there are no known studies utilising morphoscopic standards specific to the Indonesian population. Craniometric analyses can often be time-consuming; morphoscopic assessments are quicker and are also known to be reliable and accurate. One of the most utilised morphoscopic standards for the estimation of skeletal sex is that of Walker (2008). Its application across population groups demonstrated reduced accuracies outside of the United States; population-specific predictive models would thus serve to improve the identification process of unknown skeletal remains. Digital imaging also allows for the validation of standards on a contemporary population and is an appropriate proxy to physical skeletal material. The present study quantifies the applicability of the Walker standard to a contemporary Indonesian population. A total of 200 cranial MSCT scans from a hospital in Makassar were analysed using OsiriX®. Scoring was performed in accordance with the Walker standard. Five univariate and nine multivariate predictive models were derived using single trait and multi-trait combinations. The best performing univariate model included the glabella, with a total classification accuracy of 82.0% and a sex bias of 14.6%. Classification accuracy with all traits considered was at 95.2% for females and 82.8% for males with a sex bias of 12.5%. These results provide forensic practitioners in Indonesia with an appropriate morphoscopic sex estimation standard, strengthening their capabilities in the field and improving judicial outcomes. [ABSTRACT FROM AUTHOR]

In forensic anthropology, osteological sex estimation methods are continuously reevaluated and updated to improve classification accuracies. Therefore, to gain a comprehensive understanding of recent trends in sex estimation research in forensic anthropology, a content analysis of articles published between 2000 and 2022 in Forensic Science International, the Journal of Forensic Sciences, the International Journal of Legal Medicine, the American Journal of Biological Anthropology, and Forensic Anthropology, was performed. The main goals of this content analysis were to (1) examine trends in metric versus morphological research, (2) examine which areas of the skeleton have been explored, (3) examine which skeletal collections and population affinities have been most frequently utilized, and (4) determine which statistical methods were commonly implemented. A total of 440 articles were coded utilizing MAXQDA and the resulting codes were exported for analysis. Statistical analyses were conducted utilizing the Cochran‐Armitage and Jonckheere‐Terpstra tests for trends, as well as Fisher–Freeman–Halton tests. The results demonstrate that sex estimation research published in these journals has prioritized metric over morphological methods. Further, the most utilized skeletal regions continue to be the skull and pelvis, while the most popular classification statistics continue to be discriminant function analysis and logistic regression. This study also demonstrates that a substantial portion of research has been conducted utilizing U.S. and Europe‐based collections and limited populations. Based on these results, future sex estimation research must continue exploring the use of long bones and other postcranial elements, testing newer methods of analysis, as well as developing population‐inclusive methods. [ABSTRACT FROM AUTHOR]

Determining an individual's sex is crucial in several fields, such as forensic anthropology, archaeology, and medicine. Accurate sex estimation, alongside the estimation of age at death, stature, and ancestry, is of paramount importance for creating a biological profile. This profile helps narrow the potential pool of missing persons and aids identification. Our research focuses on the second cervical vertebra and odontoid process, which is particularly valuable due to their high sexual dimorphism. This brief research is structured as follows: we provide an overview of morphometric analysis of the second cervical vertebra for accurate sex estimation in forensic anthropology. We then delve into a case report to explore sexual dimorphism of the C2 vertebrae. Moreover, we discuss some of these studies that showed a significant correlation between the dimensions of the second cervical vertebrae and height, suggesting that the C2 can be used as a reliable indicator for stature estimation. The high accuracy rate of sex estimation using the second cervical vertebrae suggests that this method is a valuable tool for forensic anthropologists. Its practical application can significantly contribute to identifying and profiling individuals in a forensic context, thereby aiding in the identification process. [ABSTRACT FROM AUTHOR]

Introduction: Estimation of sex from skeletal remains is an important initial medicolegal aspect of forensic and anthropological examination. Among various methods of sex estimation only DNA analysis gives absolute proof of sex estimation, but such methods are meticulous, immoderate and relatively prolonged and involves difficult DNA extraction technique. Teeth are strongest and toughest structure in the human body which are resistance to fire, decomposition and many other changes and teeth development completed before bone maturation making teeth relevant sex indicator hence teeth can be used for sex estimation. The 1st molar tooth is suitable tooth since it erupts early and very little chance of impaction than other teeth. Aim: The aim of our study was to evaluate the sex estimation by mesiodistal width of mandibular and maxillary 1st molar teeth in north Indian population. Materials and Methods: The sample comprised of dental impression from 106 individuals (53 males and 53 females), all young adults between 20 and 35 years of age. Impressions of the teeth were made using irreversible hydrocolloid (alginate) material and casts poured in dental stone. Mesiodistal (MD) dimensions of mandibular and maxillary 1st molar of both right and left side were measured by digital caliper. Results: Data were summarized as Mean and SD. Groups (in Gender Male vs female) were compared by unpaired or independent Student's t test. Mean maxillary width of 1st molar of both right and left side were higher in male than female but were statistically not significant whereas mean of maxillary 1st molar width of right side though slightly higher in male than female but was statistically not significant whereas of left side mean was lower in male than female and statistically not significant in young north Indian population. Very little sexual dimorphism shown by maxillary and mandibular 1st molar. Conclusion: The study confirmed that maxillary and mandibular 1st molar did not establish a tool for sex estimation in north Indian populations since there was no statistically significant difference in mesiodistal width of mandibular and maxillary 1st molar among males and females on both the right and the left sides jaw. [ABSTRACT FROM AUTHOR]

This study investigated the use of 3D postmortem computed tomography (PMCT) images of the first and second ribs for sex estimation in a Japanese population. Sex estimation models using conventional discriminant analysis and ten machine learning algorithms including logistic regression (LR), Naive Bayes (NB), K-Nearest Neighbors (KNN), decision tree (DT), random forest (RF), support vector machine (SVM), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), artificial neural network (ANN), and extra tree (ET), were achieved from PMCT measurements of the first and second rib and the accuracy of models were compared. The results showed that ML algorithms, particularly LR, outperformed discriminant analysis, achieving an accuracy of 83.6 % compared to 79.1 % for stepwise discriminant analysis. This study highlights the potential of 3D PMCT and ML for accurate sex estimation in forensic anthropology.

One crucial aspect of a forensic procedure is sex estimation during individual identification. Hand and its remains are usually among the common body parts found in scenes of mass disasters during forensic investigations. Hand outlines are also important in several biomedical fields such as prosthetics, plastic surgery, and ergonomics. This cross-sectional study was done to investigate sexual dimorphism and discriminate sex using hand and hand print dimensions of 283 male and 317 female subjects who were randomly selected. Bare hand measurement and bilateral hand prints were obtained using Vernier caliper, inked pad, and A4 plain paper. Data obtained were analyzed using SPSS version 23.0 IBM. Sexual dimorphism in all the hand dimensions and prints of both hands were observed. The binary logistic regression model showed that in the left hand, bare left-hand breadth (BLHB) was the single best variable to discriminate sex with a percentage accuracy of 69.5 %. Bare right-hand breadth (BRHB) was the best predictor in the right hand with a percentage accuracy of 71.8 %. The predicted probabilities of the binary logistic model (BLR) for the variables that contributed best to the prediction were analyzed using the receiver operating characteristic (ROC) curve. It was observed that the BLHB and BRHB had the highest area under the curve (above 0.5) in the hand and print variables respectively. Sexual dimorphism and sex determination were established in this study using hand dimensions and prints. The BLHB and BRHB were the best sex determinants in this study. Although the accuracies of sex estimation from both hands in this study are low, it does confirm and support previous reports of handbreadth being the best variable for sex estimation.

Introduction: Sex estimation is challenging in cases where dismembered or non-intact skeletal remains are recovered. Therefore, the development of sex estimation standards using various bones that present with high recovery rates during forensic investigations, like the metatarsal bones, is needed. The usefulness of the dimensions around the metatarsal diaphyseal nutrient foramen in sex estimation has not been assessed in South African Africans (SAA), constituting the majority of the country's population. Materials and methods: Five measurements around the nutrient foramen were taken from 995 metatarsal bones (first to fifth) from 200 individual skeletons (100 males, 100 females). Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included the total length, distance from proximal end to nutrient foramen, circumference, and mediolateral and dorsoplantar diameters at the level of the nutrient foramen. Results: The original classification accuracies for multivariable functions of the stepwise and direct DFA ranged from 75.1 to 80 % and 76–79.5 % respectively. The original classification accuracies for multivariable functions of the stepwise and direct LRA ranged from 76.3% to 79.5 % and 75%–80.5 % respectively. The cross-validation classifications showed a drop of 0–2% for DFA and 0.2–1.9 % for LRA. Overall breadth measurements showed better classification accuracies than length measurements and females were classified with higher accuracy rates than males. Conclusion: The dimensions around the nutrient foramen of the metatarsal bones show sexual dimorphism in the SAA. The generated DFA and LRA functions produced high average classification accuracies which can be appropriate for use in sex estimation in forensic settings, especially when an isolated foot is recovered.

Abstract Background The aim of this study, which was based on this hypothesis, was to estimate sex and age by using a machine learning algorithm (ML) and artificial neural networks (ANN) with parameters obtained from the eyeball. The study was conducted on corneal topography images of 155 women and 155 men aged between 6 and 87 who did not have surgical intervention or pathology in their eyeballs. In the study, the individuals were divided into four different age groups 6–17, 18–34, 35–55, and 56–87. Sex and age estimation was carried out by using the numerical data of parameters obtained as a result of corneal topography imaging in ML and ANN inputs. Results As a result of our study, in sex determination, a 0.98 accuracy rate (Acc) was obtained with the logistic regression algorithm, one of the ML algorithms, and 0.94 Acc was obtained with the MLCP model, one of the ANN algorithms; in age estimation, 0.84 Acc was obtained with RF algorithm, one of the ML algorithms. With the SHAP analyzer of the Random Forest algorithm, through which the effects of parameters on the overall result are evaluated, the parameter that made the highest contribution to sex estimation was found to be corneal volume, and the parameter that made the highest contribution to age estimation was found to be pupil Q parameter. Conclusion As a result of our study, it was found that parameters obtained from the eyeball showed a high accuracy in sex and age estimation.

Background: The aim of this study, which was based on this hypothesis, was to estimate sex and age by using a machine learning algorithm (ML) and artificial neural networks (ANN) with parameters obtained from the eyeball. The study was conducted on corneal topography images of 155 women and 155 men aged between 6 and 87 who did not have surgical intervention or pathology in their eyeballs. In the study, the individuals were divided into four different age groups 6–17, 18–34, 35–55, and 56–87. Sex and age estimation was carried out by using the numerical data of parameters obtained as a result of corneal topography imaging in ML and ANN inputs. Results: As a result of our study, in sex determination, a 0.98 accuracy rate (Acc) was obtained with the logistic regression algorithm, one of the ML algorithms, and 0.94 Acc was obtained with the MLCP model, one of the ANN algorithms; in age estimation, 0.84 Acc was obtained with RF algorithm, one of the ML algorithms. With the SHAP analyzer of the Random Forest algorithm, through which the effects of parameters on the overall result are evaluated, the parameter that made the highest contribution to sex estimation was found to be corneal volume, and the parameter that made the highest contribution to age estimation was found to be pupil Q parameter. Conclusion: As a result of our study, it was found that parameters obtained from the eyeball showed a high accuracy in sex and age estimation. [ABSTRACT FROM AUTHOR]

The biological profile estimation is the first step toward positive identification. However, it is not always possible to access a complete and well-preserved skeleton due to postmortem damage and taphonomic changes. As such, there is a need to develop new alternatives to analyze different bones of the human skeleton. The present study aims to analyze the patellar osteometry, with attention to its degree of sexual dimorphism, to establish a simple method for estimating sex in Portuguese adults. Six measurements were taken from 222 patella pairs, including 117 females and 105 males from the XXI Century Identified Skeleton Collection of the University of Coimbra. Subsequently, this method was validated in a different sample of 50 individuals equally representing both sexes. Maximum height stands out with a 77.0% of correct sex estimation, reaching 98.0% when applied to the new sample. The linear discriminant function analysis containing all the six variables showed the best results, with 80.2% of correct classification after cross-validation and 96.0% when applied to the independent sample. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the DSP method's applicability to Romania's contemporary population and to assess the accuracy and reliability of variables derived from CT images. A total of 80 pelvic CT scans were analyzed. Participants ranged from 22 to 93 years, with a mean age of 59.51 ± 22.7 years. All variables measured from the CT scans were analyzed using DSP software. The study found that sex estimation was possible in 71.25% of cases overall, with varying rates between males (57.50%) and females (85%). Despite encountering undetermined specimens comprising 42.5% males and 15% females, only one misclassification occurred. Regarding accuracy, the overall rate remained notably high at 98.24%. All female specimens that could be estimated were correctly classified (100% accuracy), while for males, the accuracy rate was 95.65%. Undetermined cases were noted to potentially impact the accuracy of sex classification, underscoring the critical role of precision in forensic contexts. In conclusion, the study highlights the importance of accuracy in forensic sex estimation. It emphasizes the confidence with which DSP software can be utilized, if not the only method, at least as a preliminary or adjuvantly accurate technique for sex estimation in forensic anthropology. [ABSTRACT FROM AUTHOR]

The study aims to demonstrate the success of deep learning methods in sex prediction using hyoid bone. The images of people aged 15-94 years who underwent neck Computed Tomography (CT) were retrospectively scanned in the study. The neck CT images of the individuals were cleaned using the RadiAnt DICOM Viewer (version 2023.1) program, leaving only the hyoid bone. A total of 7 images in the anterior, posterior, superior, inferior, right, left, and right-anterior-upward directions were obtained from a patient's cut hyoid bone image. 2170 images were obtained from 310 hyoid bones of males, and 1820 images from 260 hyoid bones of females. 3990 images were completed to 5000 images by data enrichment. The dataset was divided into 80 % for training, 10 % for testing, and another 10 % for validation. It was compared with deep learning models DenseNet121, ResNet152, and VGG19. An accuracy rate of 87 % was achieved in the ResNet152 model and 80.2 % in the VGG19 model. The highest rate among the classified models was 89 % in the DenseNet121 model. This model had a specificity of 0.87, a sensitivity of 0.90, an F1 score of 0.89 in women, a specificity of 0.90, a sensitivity of 0.87, and an F1 score of 0.88 in men. It was observed that sex could be predicted from the hyoid bone using deep learning methods DenseNet121, ResNet152, and VGG19. Thus, a method that had not been tried on this bone before was used. This study also brings us one step closer to strengthening and perfecting the use of technologies, which will reduce the subjectivity of the methods and support the expert in the decision-making process of sex prediction. [ABSTRACT FROM AUTHOR]

Anthropologists have led the way in formulating techniques that reveal skeletal differences between males and females. Understanding of physical differences in the pelvis related to childbirth, hormonal impacts on bones, and extensive comparative studies have provided anthropologists with an array of traits and measurements that help them estimate sex using just bones. Forensic anthropologists and bioarcheologists are improving their ability to differentiate males and females by increasing research on a variety of postcranial bones and through the use of molecular data, especially new methods called proteomics, to identify sex in prepubescent juveniles. As remains from more cultures and time periods are studied, sex identification will continue to improve, because skeletal sex differences are in large part biologically determined. Yet, anthropologists have also been at the forefront of arguing that sex lies on a spectrum. Anthropologists who view sex as on a spectrum may deter sex identification progress; from their perspective, an individual of an undetermined sex may just be a nonbinary individual. Anthropologists who consider sex is on a spectrum are coming to this conclusion in part because they are looking for anatomical ideals, mistaking pathology for variation, and confusing independent variables with dependent variables. Nonetheless, anthropologists need to continue to improve sex identification techniques to reconstruct the past accurately, which may reveal less strict sex roles than previously presumed and help with the identification of crime victims. Forensic anthropologists should also increase their efforts to identify whether individuals have undergone medical procedures intended to change one's gender due to the current rise in transitioning individuals. [ABSTRACT FROM AUTHOR]

The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed. A saliency map was generated by gradient-weighted class activation mapping for each output. The two deep learning models achieved high values in each performance metric according to accuracy, sensitivity (recall), precision, F1 score, and areas under the receiver operating characteristic curve. Both models showed substantial differences in the positions indicated in saliency maps for male and female images. The positions in saliency maps also differed between VGG16 and DenseNet-121, regardless of sex. This analysis of our proposed system suggested that sex estimation from lateral cephalograms can be achieved with high accuracy using deep learning. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this paper is to assess the determination of male and female sex from trabecular bone structures in the pelvic region. The study involved analyzing digital radiographs for 343 patients and identifying fourteen areas of interest based on their medical significance, with seven regions on each side of the body for symmetry. Methods: Textural parameters for each region were obtained using various methods, and a thorough investigation of data normalization was conducted. Feature selection approaches were then evaluated to determine a small set of the most representative features, which were input into several classification machine learning models. Results: The findings revealed a sex-dependent correlation in the bone structure observed in X-ray images, with the degree of dependency varying based on the anatomical location. Notably, the femoral neck and ischium regions exhibited distinctive characteristics between sexes. Conclusions: This insight is crucial for medical professionals seeking to estimate sex dependencies from such image data. For these four specific areas, the balanced accuracy exceeded 70%. The results demonstrated symmetry, confirming the genuine dependencies in the trabecular bone structures. [ABSTRACT FROM AUTHOR]

The lateral angle method of sex estimation is tested on an archaeological population with genetic sex estimates. Casts of the internal auditory canal were made using a quick drying impression material on 90 individuals (76 adults and 14 nonadults) from Anglo‐Saxon and Medieval Cambridgeshire. The anterior and posterior angles of the internal auditory canal were measured, and the relationship of the angle to genetic sex was tested. The posterior angle failed intra‐observer error tests, and only the anterior angle could be analysed. Using the previously published sectioning point for unburnt remains (45°), the method did not adequately distinguish between the sexes. Furthermore, the difference between male and female was insufficient to create population‐specific discriminant functions. The anterior angle does not meet the requirements for an osteological method of sex estimation, exhibiting no statistical correlation with genetic sex in this population. [ABSTRACT FROM AUTHOR]

Introduction: Sex estimation is crucial in forensic anthropology. In situations such as mass disasters, and forensic anthropology cases, sex estimation is a very important initial step in the disaster victim identification process. Literature has acknowledged that sex estimation is population-specific. However, sex estimation standards in South-East Asian populations are limited, leading to the usage of most Thais discriminant function equations on sex estimation by other South-East Asian countries including Malaysia. This systematic review was conducted to summarise the findings of sex estimation studies in South-East Asian countries. Materials and Methods: A systematic literature search was performed through the SCOPUS database and Web of Science (WOS) database for relevant studies between 2014 and 2022. All published articles that are related to sex estimation from different types of bone, methods, landmarks, and sample sources (i.e., photographs, dry bones, and CT images) were included in this review. The main inclusion criteria were studies on (i) sex estimation; (ii) in South-East Asian populations; (iii) between the years 2014 and 2022; and (iv) in English. Results: The literature search identified 30 potentially relevant studies, of which 15 publications met all the inclusion criteria. From those research, 13 studies were related to the Thai population and two to the Malaysian population. Only one study was based on morphological traits, while the rest were based on a morphometric approach. Conclusion: All studies found that sex estimation is populationspecific. Therefore, further research is recommended to explore more on population-specific sex estimation using different parts of bone. [ABSTRACT FROM AUTHOR]

Introduction:Various methods of identification such as anthropometry, stature estimation, dactylography, sex estimation, age estimation, DNA analysis, differentiation by blood groups and odontology are used in forensic medicine to create biological profile of an unknown individual. Estimation of sex is the first step towards identification of person. Determination of sex from skeletal remains is an essential task in medicolegal examination. Teeth are highly indestructible and reveal minimal turnover of natural substance hence teeth can be used for sex estimation.Mesiodistal parameter of mandibular and maxillary canine gave evidence of sex estimation due to sexual dimorphism. Aim: The aim of our study was to evaluate the sex estimation by mesiodistal width of mandibular canine and mesiodistal width of maxillary canine in north Indian population. Materials and Methods: The sample comprised of dental impression from 120 individuals (60 males and 60 females), all young adults between 20 and 35 years of age. Impressions of the teeth were made using irreversible hydrocolloid (alginate) material and casts poured in dental stone. Mesiodistal (MD) dimensions of mandibular and maxillary canine of both right and left side is measure by caliper. Results: Mean mandibular canine width of both right and left sidewere higher in male than female and were statistically significant whereas, mean maxillary canine width of both right and left side were slightly higher in male than female but were not statistically significant in young north Indian population. Left mandibular canine width (6%) was more sexually dimorphic than right mandibular canine width (5.1%). Whereas negligible sexual dimorphism shown by maxillary canine. Conclusion: The study confirmed that among maxillary and mandibular canine, mandibular canine can be used for sex estimation and shows significant sexual dimorphism. [ABSTRACT FROM AUTHOR]

Scoping reviews in forensic odontology and dental anthropometry provide valuable information. Several current studies indicate different three-dimensional (3D) scanning and digital technologies in clinical dentistry. However, there is a paucity of literature on the utilization and performance of 3D scanner technologies in forensic science and/or medico-legal settings. This study undertook a scoping review of the 3D technologies utilized while researching the applied anatomy of the dentition of modern human forensics. The objectives of this study were to identify which 3D technologies are/were used to determine best practices in usage for research of the dentition of humans and to identify the gaps and challenges faced in the utilization of 3D technologies in dental research covering the forensic domains. Twenty-four key phrases were used in this study to search four databases for the period 1973 to 2023. The initial search yielded 6782 articles, which was then reduced to 1043 after removing any duplicate articles. After title and abstract screening, 35 articles were featured, this was further reduced to 24 articles after applying the selection criteria. The results highlighted the following gaps and challenges faced in the utilization of 3D technologies in dental forensic research: the lack of utilization of 3D equipment for forensic application, as no studies were noted to have been conducted within an African context; a disparity between studies in the Northern and Southern hemispheres, with many studies concentrated in the European and Far East regions and a lack of 3D resources in Africa coupled with the lack of specialized personnel trained to utilize the equipment if available optimally. The scanning modality frequently appears is the 3D Cone Beam Computed Tomography (3D CBCT). Intraoral scans and 3D scanning of dental casts coupled with 3D Geometric Morphometrics were also noted to have been used.

Background: Sex and/or ancestry estimations based on skeletal elements are vital in forensics, as these variables are key to identification of unknown skeletal remains. Unfortunately, patterns of skeletal variation are often shared between sex and ancestry groups, making independent estimation of such variables less accurate, especially when substantial size differences exist both within and between groups. Geometric morphometric analysis allows isolation of the size component of variation, enabling independent and more sensitive detection of shape variation between groups. This creates the potential for more accurate estimations of sex and ancestry either independently or simultaneously, thus reducing the chances of compounding errors of estimation. This would be especially beneficial in heterogeneous populations, such as that of South Africa, where group separation may be affected by complicated genetic and environmental influences. Methods: This study assessed sex and ancestry variation in morphology of 1894 ulnae of South African males and females of the country's three largest ancestry groups. Three-dimensional data was submitted to Generalized Procrustes Analysis for superimposition and scaling to a common centroid size. Mean centroid sizes and shapes were compared, and accuracy of sex, ancestry, or sex-ancestry estimation was assessed using Discriminant Function Analysis and leave-one-out cross-validation. Covariation with size, age and year-of-birth were assessed through regression analysis. Results: Male ulnae were absolutely and proportionally larger than female ulnae, while Black individuals were similarly larger than Colored and White individuals. Based on this variation, sex could be estimated with 68.8 % accuracy, and ancestry with 73.6 % accuracy. Simultaneous sex-ancestry assessment showed similar morphological patterning and yielded a mean classification accuracy of 73.6 %. Conclusions: These results have practical value for forensic application, where relatively poorly elements such as the ulna are often all that is available for analysis. Additionally, simultaneous estimation of sex and ancestry reduces compounding errors that may arise from first estimating one variable and basing the rest of the biological profile estimations thereon. Such improved estimations are of great potential value, especially in heterogeneous populations such as that of South Africa.