A hybrid convolutional neural network model for dental age estimation using buccal alveolar bone level for Saudi children

A hybrid convolutional neural network model for dental age estimation using buccal alveolar bone level for Saudi children

Abstract Background Age estimation is an essential task in medical dentistry and forensic sciences. Dental Age Estimation (DAE) is one of the most common methods for age estimation. Teeth are commonly used for age estimation because the schedules of tooth development and eruption are barely affected...

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Main Authors: Seyed Matin Mazloom Nezhad, Erma Rahayu Mohd Faizal Abdullah, Norliza Ibrahim, Heba H. Bakhsh, Uzair Ishtiaq, Rabiah Al Adawiyah Rahmat, Sarah AlMugairin, Sara M. ElKhateeb
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Oral Health
Subjects:
Age estimation
Dental age
Machine learning
Deep learning
Buccal alveolar bone level
Support vector machine
Online Access:https://doi.org/10.1186/s12903-025-06694-9
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https://doi.org/10.1186/s12903-025-06694-9

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