Satish Vishwanathaiah

Successful outcome of pulp therapy depends on good chemomechanical preparation of the canals. This is completed with the help of various upcoming rotary and hand files. However, during this preparation, there might be an apical extrusion of the debris which may result in postoperative complications. The aim of this study was to evaluate and compare the number of debris apically extruded during canal preparation using two different pediatric rotary file systems and conventional hand file systems in primary teeth. 60 primary maxillary central incisors that were extracted due to trauma or untreated dental caries with no signs of resorption were taken. Canal preparation was executed using three different file systems: Group A: Group A hand K file system, Group B Kedo S Plus, Group C Kedo SG Blue. For each of these files using the Myers and Montgomery model, the pre- and post-weight of the eppendorf tube was assessed to quantify the number of apical debris. The maximum extrusion of apical debris was noticed with the Hand K-file system. The least debris was noticed in the Kedo S Plus file system. Statistical analysis revealed that there were highly significant differences in apical extrusion and debris when comparing hand files and rotary files and also between the two rotary files used. Apical debris collection is an unavoidable outcome of canal instrumentation. Among the file systems compared, rotary files had lesser extrusion when compared to hand files. Among the rotary files, Kedo S plus showed normal extrusion compared to SG Blue.

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan.