Application of deep learning in evaluating the anatomical relationship between the mandibular third molar and inferior alveolar nerve: A scoping review

Deep learning shows promising potential in the radiographic evaluation of mandibular third molars. To date, most studies have relied on two-dimensional images and focused on detection and segmentation, while predictive modeling and three-dimensional CBCT-based analysis are relatively limited. To enhance clinical utility, larger standardized datasets, transparent multi-expert annotation, task-specific benchmarking, and robust external/multicenter validation are needed. These measures will enable reliable pre-extraction risk prediction and support clinical decision-making.