In forensics, predicting the sex is a crucial step in identification. Many studies have aimed to find an accurate and fast technique to estimate the sex. This study was conducted to determine the accuracy of volumetric and linear measurements of three-dimensional (3D) images of the mandible obtained from cone beam computed tomography (CBCT) radiographs, using different machine-learning (ML) models for sex identification. The CBCTs of 104 males and 104 females were included in this study. The radiographs were converted to 3D images, and the volume, surface area, and ten linear measurements of the mandible were obtained. The data were evaluated using statistical analysis and five different ML algorithms. All results were considered statistically significant at p < 0.05, and the precision, recall, f1-score, training accuracy, and testing accuracy were used to evaluate the performance of the ML models. All the studied parameters showed statistically significant differences between sexes p < 0.05. The right coronoid-to-gonion linear distance had the highest discriminative power of all the parameters. Meanwhile, Gaussian Naive Bayes (GNB) showed the best performance among all the ML models. The results of this study revealed promising outcomes; the sex can be easily determined, with high accuracy (90%).

This study aimed to predict the skeletal growth maturation using convolutional neural network-based deep learning methods using cervical vertebral maturation and the lower 2nd molar calcification level so that skeletal maturation can be detected from orthopantomography using multiclass classification. About 1200 cephalometric radiographs and 1200 OPGs were selected from patients seeking treatment in dental centers. The level of skeletal maturation was detected by CNN using the multiclass classification method, and each image was identified as a cervical vertebral maturation index (CVMI); meanwhile, the chronological age was estimated from the level of the 2nd molar calcification. The model’s final result demonstrates a high degree of accuracy with which each stage and gender can be predicted. Cervical vertebral maturation reported high accuracy in males (98%), while females showed high accuracy of 2nd molar calcification. CNN multiclass classification is an accurate method to detect the level of maturation, whether from cervical maturation or the calcification of the lower 2nd molar, and the calcification level of the lower 2nd molar is a reliable method to trust in the growth level, so the traditional OPG is enough for this purpose.

Background: Identifying the prevalence of orofacial malignancies is essential to provide health-care programs and services for a specific population. This study aimed to specify the prevalence, clinical and histopathological features of oral malignancies in Sulaimani for over 12 years.Methods: All archived reports for orofacial specimens from 2008 to 2019 were collected from three major centers in Sulaimani governorate. The demographic data, date, type of surgery, lesion's site, and diagnosis were recorded. The ICD-10 coding was specified for each case. A Chi-square test was used to assess differences between genders. A one-way ANOVA test was applied to analyze the differences in mean age distributions among different sites of oral malignancies and oral squamous cell carcinoma histopathological grades.P < 0.05 was considered significant.Results: Orofacial malignant lesions account for 14.53% of the total sample. Patients' mean age was (55.46 ± 18.48) years, and they were predominantly males (M: F ratio = 1.15:1). The tongue was the frequently affected site (14.8%). A Chi-square test showed no significant difference between genders concerning age (P = 0.118), years of registration (P = 0.28), and site (P = 0.29). The C06 (represents; cheek mucosa C06.0, the vestibule of mouth C06.1, retromolar area C06.2, and other unspecified parts of mouth C06.8) was the most frequent topographical ICD-code (18.1%). Carcinoma was a frequent malignancy (63.2%). OSCC was the most common lesion (56.4%). It commonly affects males, and the tongue was the frequent site (24.1%) followed by lip (17.8%).Conclusions: There is a slight increase in the registered oral malignancies in Sulaimani city over 12 years; they were predominated in males, in 61–70 years old patients, and being oral squamous cell carcinoma types.

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This study evaluates the cytomorphometric measures of cells obtained from the buccal mucosa of dental students to assess the fluctuation of the cellular characteristics among relatively normal subjects, with any potential correlations with demographic information, different habits, and hormonal disturbance. This prospective study included 100 dental students with no detectable oral alterations submitted to brush cytology. The smears were fixed with 95% ethyl alcohol and stained with hematoxylin and eosin stain. The stained section was observed under an image analyzer for cytomorphometric analysis. Cytopathological observations were recorded, including inflammation, microbial colonies, micronuclei, keratinization, overlapping, and hemorrhage. Chi-square tests were applied for non-parametric variables. One-way analysis of variance (ANOVA) was used to compare the cytometric parameters to habits and hormonal disturbances. A p-value < 0.05 was considered statistically significant. The results showed close proximity among subjects in the matter of cytomorphometric measures; no significant influence of sex, smoking, alcohol drinking habits, and menstruation was found on cytomorphometric diameters or cytopathological observation, and vice versa, while polycystic ovary syndrome impacted nuclear and nuclear-cytoplasmic ratio (p = 0.003, p = 0.02), respectively. Oral exfoliative cytology combined with cytomorphometric analysis for the studied normal individuals can be helpful in various investigations of oral and systemic diseases.

Oral and maxillofacial lesions (OMFLs) in pediatrics differ markedly from their adult counterparts in terms of clinical conduct, pathological behavior, and management. This study aims to determine the frequency of OMFLs among pediatric and adolescent patients and to correlate the demographics information to the site, and histopathological findings. Pathological records of pediatric and adolescent patients were retrieved from three major pathological centers in Sulaimani city of Iraq. Demographic information, surgical procedure, anatomical sites, and histopathological diagnosis were recorded. Furthermore, The World Health Organization (WHO) International Statistical Classification of Diseases and Related Health Problems (ICD-10) was used for coding. A Chi-square test was used to find the relation between different variables, and a p-value < 0.05 was considered statistically significant. This study archived 309 (13.3%) out of 2319 pediatric and adolescent patients, with a mean age of 11.04 ± 4.62. Females were more commonly detected (52.8%). The most frequently diagnosed lesions were salivary gland diseases (20.7%), followed by reactive hyperplastic connective tissue (18.4%). A significant relation was found between age groups and diagnostic categories (p = 0.001). The lips were the most commonly detected sites (20.7%). Mucocele was the most frequently seen non-neoplastic lesions (19.4%), followed by pyogenic granuloma (8.7%). Neoplastic lesions revealed predominant hemangioma (3.2%), followed by peripheral ossifying fibroma (1.9%). Traumatic and or reactive lesions were the most commonly reported lesions. Malignant neoplasms can be identified. The current study enabled systematic data recording of pediatric and adolescent patients, encouraging the importance of the oral healthcare system in identifying and managing the problem early in this critical age in this region.