Deep learning-based approach to third molar impaction analysis with clinical classifications

Deep learning-based approach to third molar impaction analysis with clinical classifications

Abstract This study developed a deep learning model for the automated detection and classification of impacted third molars using the Pell and Gregory Classification, Winter’s Classification, and Pederson Difficulty Index. Panoramic radiographs of patients treated at Sivas Cumhuriyet University betw...

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Bibliographic Details
Main Authors: Yunus Balel, Kaan Sağtaş
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Impacted third molar
Artificial intelligence
Deep learning
Detection
Classification
Online Access:https://doi.org/10.1038/s41598-025-93783-y
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https://doi.org/10.1038/s41598-025-93783-y

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