ACCURACY AND DIAGNOSTIC EFFICIENCY OF ARTIFICIAL INTELLIGENCE ALGORITHMS IN THE ANALYSIS OF DENTAL RADIOGRAPHS

Abstract

This comprehensive scientific article explores the application of artificial intelligence (AI) systems in the analysis of digital radiographs, one of the most pressing and promising areas of modern dentistry. The primary objective of the study is to comparatively analyze the accuracy of algorithms based on Deep Learning and Convolutional Neural Network (CNN) architectures in detecting dental caries, periapical inflammatory processes, complex root canal anatomy, and alveolar bone resorption. The article scientifically substantiates the algorithmic precision of AI systems in minimizing diagnostic errors related to human factors, such as subjective fatigue of the physician, high workload, or limitations in visual perception. The research results indicate that AI systems demonstrate high efficiency in identifying pathological changes that may be overlooked by clinicians, especially destructive processes at an early stage. The article concludes by highlighting the role of implementing this technology in Uzbek dental practice for standardizing diagnostic quality and increasing physician productivity.