Artificial intelligence (AI) has become an increasingly valuable tool in dental imaging, particularly for the analysis of radiographs and cone-beam computed tomography (CBCT) scans. This paper reviews the current applications and effectiveness of AI algorithms, especially deep learning models, in detecting dental pathologies and anatomical structures. The integration of AI enhances diagnostic accuracy, reduces human error, and streamlines clinical workflows. Despite challenges such as dataset limitations and the need for standardized protocols, AI demonstrates substantial potential to transform dental diagnostics. Continued research and development are essential for optimizing AI tools and promoting their widespread adoption in clinical practice.

Artificial Intelligence, Dental Radiography, Cone-Beam Computed Tomography

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