AI-assisted gender prediction from the jawbone using CBCT measurements

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study uses pre-existing CBCT scans from adult Egyptian patients to create a deep learning model that automatically identifies anatomical points, takes specified mandibular measurements, and predicts gender. The model’s performance will be compared against the known gender in patient records, and its ability to match radiologist measurements will be evaluated. The primary goal is to measure accuracy, precision, and recall of the AI in gender determination, with a secondary aim to assess the AI’s accuracy in anatomical point placement and measurements. The study leverages automated mandibular segmentation and three-dimensional neural networks to test whether AI can assist forensic odontology workflows.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Scans belonging to patients above or at the age of 18 years (≥ 18 years)
* Scans that image the area of interest clearly (mandible) with a craniofacial or maxillomandibular field of view.
* Good quality of the scan with no artefacts

Exclusion Criteria:

* CBCT scans with significant artifacts (e.g. metal artefact) affecting visualization of the mandible
* Congenital craniofacial anomalies affecting the mandibular anatomy
* Large pathologies that affect the mandible's dimensions and cause significant bone loss.
* Trauma to the mandible

Where it's running

• Faculty of Dentistry, Cairo University
  Cairo, Egypt Recruiting

Study contacts

• Study coordinator: Ashrakat Abdelmonem Habib, Master's candidate
• Email: ashrakat.habib@dentistry.cu.edu.eg
• Phone: +201146752225

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.