The relevance of the study is due to the active introduction of digital technologies into clinical dentistry and the need to improve the accuracy, aesthetic predictability and personalization of orthopedic treatment. Tooth loss, especially in an aesthetically significant area, requires an integrated approach combining morphometric analysis of the face, assessment of occlusal relationships and modern digital modeling methods. As patients' demands on the quality and appearance of orthopedic structures increase, the role of digital tools is increasing, allowing clinicians to visualize the result of treatment in advance and increase communication between the doctor, dental technician and patient. The purpose of the work is to determine the functionality of computer programs designed for modeling teeth in an aesthetically significant area based on the analysis of information sources, as well as to evaluate their role in improving the effectiveness of orthopedic rehabilitation. The study used photometric, cephalometric and 3D scanning methods to obtain anthropometric data of the face and dentition. The analysis was carried out using modern software solutions (Digital Smile Design, 3Shape Smile Design, Avantis 3D, SmileCloud), providing modeling of orthopedic structures taking into account the individual characteristics of the patient. The results and discussion showed that the use of existing programs makes it possible to increase the accuracy of digital planning, reduce the number of clinical treatment stages, minimize subjective errors of the doctor and improve the aesthetic reproducibility of orthopedic structures. The use of artificial intelligence algorithms contributes to a personalized choice of the shape, size and position of teeth, as well as an optimal match between the morphology of the face and dentition. The conclusion emphasizes that the introduction of computer technologies for virtual modeling contributes to the transition to a new paradigm of dental rehabilitation, personalized digital orthopedics based on the integration of clinical experience, digital data and intelligent analysis systems.
Apresyan et al. (Sun,) studied this question.