AIMC Topic: Tooth, Impacted

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Machine learning in orthodontics: .

The Angle orthodontist
OBJECTIVES: To (1) introduce a novel machine learning method and (2) assess maxillary structure variation in unilateral canine impaction for advancing clinically viable information.

Automated detection of third molars and mandibular nerve by deep learning.

Scientific reports
The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and subsequent sensory disturbances of the lower lip and chin following the removal of third molars. To a...

Predicting postoperative facial swelling following impacted mandibular third molars extraction by using artificial neural networks evaluation.

Scientific reports
Patients' postoperative facial swelling following third molars extraction may have both biological impacts and social impacts. The purpose of this study was to evaluate the accuracy of artificial neural networks in the prediction of the postoperative...

Artificial intelligence-based automated preprocessing and classification of impacted maxillary canines in panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVES: Automating the digital workflow for diagnosing impacted canines using panoramic radiographs (PRs) is challenging. This study explored feature extraction, automated cropping, and classification of impacted and nonimpacted canines as a firs...

Amelogenesis Imperfecta with Coronal Resorption: Report of Three Cases.

Dental update
Intracoronal resorption of the permanent dentition in cases of amelogenesis imperfecta (AI) is a rare finding which poses an added complication to the already complex management of this condition. This paper presents three cases of AI associated with...