Diagnostic accuracy of artificial intelligence tools in evaluating the inferior alveolar nerve-third molar relationship: a systematic review.
A B Teodoro, R Fedato, K Evangelista et al.
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In 30 seconds
This systematic review evaluated the diagnostic accuracy of artificial intelligence (AI) tools in assessing the relationship between the inferior alveolar nerve (IAN) and third molars. The review included 17 studies with approximately 22,211 third molars. AI tools showed relatively high accuracy, although the evidence quality was low, particularly for cone-beam CT models.
Key findings
- AI tools demonstrated relatively high accuracy in diagnosing the IAN-third molar relationship.
- Fourteen studies utilized 2D images, while three studies employed cone-beam CT for diagnosis.
- Significant heterogeneity was observed in models, imaging examinations, and classification methods across studies.
- The level of evidence certainty regarding CBCT models was low despite promising accuracy.
Why it matters
Understanding the diagnostic capabilities of AI in dental imaging can enhance decision-making for clinicians involved in oral and maxillofacial surgery. Improved accuracy in identifying nerve relationships can lead to better surgical outcomes and reduced complications.
What to keep in mind
The review noted significant heterogeneity in study methodologies and low evidence quality for cone-beam CT models.