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Validating AI for Gender Prediction Using Morphometric Analysis of the Mandible

NCT07726290 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 385

Last updated 2026-07-24

No results posted yet for this study

Summary

This retrospective validity study evaluates the accuracy of artificial intelligence (AI) in determining gender from mandibular morphometric linear measurements. The study utilizes pre-existing Cone Beam Computed Tomography (CBCT) scans of adult Egyptian dental patients. After automatic segmentation of the mandible from these scans, a radiologist will manually perform measurements from certain anatomical points. These measurements will be the reference standard for the AI models.

A three-dimensional deep learning model will be developed to perform two tasks:

1. To identify the anatomical points and make the specified linear measurements from these points on the segmented mandibles
2. To accurately predict gender based on these measurements. (Main Objective) The primary objective of this study is to evaluate the accuracy of machine learning algorithms in gender identification from linear morphometric measurements of the mandible. The known gender from patient records will serve as the reference standard.

This study will assess the reliability of AI as an objective tool for gender determination for forensic purposes.

Conditions

  • Gender
  • MANDIBLE
  • Forensic Dentistry
  • Morphometric Analysis
  • Artifical Intelligence
  • Gender Prediction

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Principal Investigators

  • Ola Mohamed Associate professor · Oral and Maxillofacial Radiology, Faculty of Dentistry, Cairo University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-03-30
Completion
2027-05-01

Countries

  • Egypt

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07726290 on ClinicalTrials.gov