MATERIAL AND METHODS: The study included 223 tomograms of the head and neck in sagittal projection from patients without any pathology of the studied structures. Morphometric analysis was carried out using PjaPro and Gradient programs, statistical analysis was performed by SPSS Statistics software. A fully convolutional EfficientNet-B2 neural network was used, which was trained in two stages: selection of the area of interest and solution of regression tasks.
RESULTS: Morphometric assessment and subsequent statistical analysis of the selected group of features have shown presence of the strongest correlation with age in the indicator characterizing the involution of the median atlantoaxial joint. A deep learning method using the convolutional network, which automatically selects the desired area in the image (the area of the vertebral junction), classifies the sample, and makes an assumption about the age of the unknown individual with an accuracy of 7.5 to 10.5 years has been tested.
CONCLUSION: As a result of the study, a positive experience has been obtained indicating the possibility of using convolutional neural networks to determine the age of the unknown person, which expands the evidence base and provides new opportunities for determining group-wide personality traits in forensic medicine.
MATERIALS & METHODS: A previously published questionnaire was used in the current survey. It was an online survey with 12 questions regarding the management of TDIs and some additional questions regarding sociodemographic and professional profiles of the participants were added. The survey was distributed to final-year undergraduate students and postgraduate students in pediatric dentistry and endodontics from 10 dental schools. Simple frequency distributions and descriptive statistics were predominantly used to describe the data. Differences in the median percentage scores among the student categories were assessed using the Kruskal-Wallis test followed by Dwass-Steel-Critchlow-Fligner pairwise comparisons.
RESULTS: A total of 347 undergraduates, 126 postgraduates in endodontics, and 72 postgraduates in pediatric dentistry from 10 dental schools participated in this survey. The postgraduates had a significantly higher percentage score for correct responses compared with the undergraduates. No significant difference was observed between the endodontic and pediatric dentistry postgraduates.
CONCLUSION: The knowledge possessed by undergraduate and postgraduate students concerning the IADT-recommended management of TDIs varied across the globe and some aspects were found to be deficient. This study emphasizes the critical importance of reassessing the teaching and learning activities pertaining to the management of TDIs.