Automated Age and Sex Estimation From Dental Panoramic Radiographs.

ABSTRACT:

Background

Age and sex estimation, which is crucial in forensic odontology, traditionally relies on complex, time-consuming methods prone to human error. This study proposes an AI-driven approach using deep learning to estimate age and sex from panoramic radiographs of Thai children and adolescents.

Methods

This study analyzed 4627 images from 2491 panoramic radiographs of Thai individuals aged 7 to 23 years. A supervised multitask model, built upon the EfficientNetB0 architecture, was developed to simultaneously estimate age and classify sex. The model was trained using a 2-phase process of transfer learning and fine-tuning. Following the development of an initial baseline model for the entire 7 to 23-year cohort, 2 primary age-stratified models (7-14 and 15-23 years) were

SUBMITTER: Sributsayakarn N 

PROVIDER: S-EPMC12557582 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature