Systematic review evaluates AI's diagnostic accuracy for periapical lesions using CBCT scans, indicating potential improvements.
This systematic review and meta-analysis aims to evaluate the diagnostic accuracy of artificial intelligence (AI) models in detecting periapical lesions on Cone-Beam Computed Tomography (CBCT) scans. The study will synthesize data from peer-reviewed literature to provide pooled estimates of sensitivity and specificity. Given the variations in units of analysis (scans vs. teeth/roots) across existing studies, subgroup analyses will be performed to assess the impact of these factors on AI performance. The review follows PRISMA-DTA guidelines.
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Chahhat (2026) studied this question.
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