Abstract

This study explores the growing role of artificial intelligence (AI) in oral and dental health, specifically in the analysis of advanced imaging techniques. Traditional methods, such as Computed Tomography (CT), Cone Beam Computed Tomography (CBCT), and X-rays, require intensive, experience-based analysis by a physician, which is both time-consuming and susceptible to human error. The text reviews current AI studies that utilize panoramic and intraoral X-ray images to automate disease detection and facilitate orthodontics. It addresses the challenges of accessing patient data and highlights the diversity of approaches in this field, including various algorithms, models, and data labeling methods, such as marking quadrants or identifying specific dental conditions like decay, missing teeth, or implants. The primary goal of this review is to consolidate existing research, providing a comprehensive overview that can inspire and guide future studies in the application of AI for dental diagnostics and treatment.

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