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  1. Home
  3. Deep Learning For Age Estimation And Sex Prediction Using Mandibular-cropped Cephalometric Images: Comparative Model Development And Validation Study.
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  3. Deep Learning For Age Estimation And Sex Prediction Using Mandibular-cropped Cephalometric Images: Comparative Model Development And Validation Study.

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Deep Learning for Age Estimation and Sex Prediction Using Mandibular-Cropped Cephalometric Images: Comparative Model

Vitria Wuri Handayani1,2, Mieke Sylvia Margaretha Amiatun Ruth3, Riries Rulaningtyas4

  • 1Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.

JMIR AI
|March 18, 2026

View abstract on PubMed

Summary
This summary is machine-generated.
Keywords:
AIage estimationartificial intelligenceartificial intelligence in medical imagingcephalometric radiographpreprocessing deep learningsex prediction

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Deep learning accurately predicts age and sex from mandibular radiographs, aiding forensic identification with partial remains. This AI-assisted approach enhances disaster victim identification capabilities.

Area of Science:

  • Forensic Odontology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Mandibular structures are key for forensic identification using partial remains.
  • Deep learning on cephalometric radiographs can predict age and sex for forensic and clinical use.

Purpose of the Study:

  • Develop and evaluate a multitask deep learning framework for age and sex prediction.
  • Analyze cropped mandibular regions from cephalometric radiographs.
  • Compare deep learning models and preprocessing techniques for demographic prediction.

Main Methods:

  • Utilized 340 Indonesian cephalometric radiographs (ages 8-40), cropping mandibular regions.
  • Applied four preprocessing scenarios including Synthetic Minority Oversampling Technique and StandardScaler.
  • Fine-tuned six pre-trained convolutional neural network backbones in a multitask framework.

    • Main Results:

    • VGG16 model showed best age estimation (MAE 3.19 years) on original data.
    • VGG16 achieved highest sex prediction accuracy (86%) with StandardScaler.
    • VGG19 also demonstrated strong performance in sex prediction (82% accuracy).

    Conclusions:

    • Integrating mandibular cropping with deep learning improves demographic prediction from radiographs.
    • AI-assisted forensic odontology can aid in disaster victim identification with partial remains.