Review: AI CBCT Analysis for Ridge Preservation Technically Feasible, Clinically Unproven

AI-driven CBCT segmentation achieves Dice scores >0.90 with faster processing for alveolar ridge preservation, but no study linked AI output to patient outcomes like implant survival or aesthetics.

• AI segmentation of teeth and alveolar bone on CBCT consistently exceeded Dice similarity coefficients of 0.90, with markedly reduced processing times.
• No included study connected AI output to patient-centered outcomes such as implant survival, aesthetics, complications, or need for re-augmentation.
• External validation was reported in only four of 17 AI studies, and reporting metrics were heterogeneous.

Automated summary

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