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

NCT05901857 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 22

Last updated 2023-06-13

No results posted yet for this study

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.

Conditions

  • Age Problem

Interventions

DIAGNOSTIC_TEST

convolutional neural network

A deep learning model for dental age classification from panoramic images

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Principal Investigators

  • Mohab Eid · Nile University

Eligibility

Min Age
6 Years
Max Age
16 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-06-30
Primary Completion
2024-01-01
Completion
2025-12-01

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 NCT05901857 on ClinicalTrials.gov