aceValidation of artificial intelligence-assisted CBCT analysis for predicting inferior alveolar nerve proximity to impacted mandibular third molars: a diagnostic accuracy study
This study aimed to evaluate the diagnostic accuracy of an artificial intelligence (AI)-assisted cone-beam computed tomography (CBCT) analysis system for predicting the spatial proximity of the inferior alveolar nerve (IAN) to impacted mandibular third molars (M3M), using expert radiologist assessment as the reference standard. A retrospective diagnostic accuracy study was conducted on an internal institutional cohort of 312 patients (mean age 28.21 ± 6.62 years; January 2021-December 2024). A deep learning syst…
An AI system using modified U-Net segmentation automatically classified inferior alveolar nerve proximity to impacted mandibular third molars on CBCT with 90.1% accuracy and reduced analysis time from ~189 seconds to ~4.8 seconds compared to expert radiologists.
Reference standard was radiographic expert assessment rather than intraoperative findings, and authors state prospective multicenter validation with surgical outcomes is needed before clinical deployment.
Evidence
- Peer-reviewedBMC Oral Health2026-08-15
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Truvace Impact Record TRV-2026-0798, v1: “Validation of artificial intelligence-assisted CBCT analysis for predicting inferior alveolar nerve proximity to impacted mandibular third molars: a diagnostic accuracy study.” Truvace, 2026-08-17. /record/TRV-2026-0798 (accessed at citation time). sha256 b99b1ee9ffcb25ab…
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