UnknownNot Applicable

Assessing the Precision of Convolutional Neural Networks for Dental Age Estimation From Panoramic Radiographs

Egypt22 participantsStarted 2023-06-30

Plain-language summary

The aim of this study is to assess the accuracy of a convolutional neural network in dental age estimation from digital panoramic radiographs. The reference standard will be the chronological age of the patient.

Who can participate

Age range6 Years – 16 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * Presence of all mandibular left permanent teeth (except third molars) * Clearly visible root development * No systemic disease * No history of root canal therapy or extraction * No related diseases affecting mandibular development such as cysts or tumors. Exclusion Criteria: * Patients with premature birth * Facial asymmetry * Congenital anomalies * History of trauma or surgery in dentofacial region

What they're measuring

Accuracy of dental age estimation from digital panoramic radiographs using CNN models

Timeframe: Through study completion, an average of 1 year

Trial details

NCT IDNCT05901857

SponsorCairo University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2024-01-01

Contact for this trial

Rawan Elkassas

+201011385738 rawanelkassas@gmail.com

View on ClinicalTrials.gov More Age Problem trials