Traditional diagnosis of dento-maxillary anomalies is a laborious, subjective, and error-prone process. The analysis of radiographs and 3D models depends on the clinician's experience, which can lead to diagnostic discrepancies among different specialists. Artificial intelligence (AI) technologies offer immense potential to address these challenges by enhancing diagnostic accuracy, automating processes, and facilitating the development of personalized treatment plans for each patient. The integration of AI into orthodontics and dentistry holds significant scientific and practical relevance for improving treatment outcomes and increasing clinical efficiency.

artificial intelligence, orthodontics, dento-maxillary anomalies, diagnosis, deep learning, machine learning, cephalometric analysis, CBCT, 3D modeling.

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