Accuracy of Detection of Dental Caries from Intraoral Images Using Different ArtificiaI Intelligence Models

February 28, 2025 updated by: Sherine Tarek Mohamed Elsayed Khaled, Cairo University

Accuracy of Dental Caries Detection from Intraoral Images Using Different Artificial Intelligence Models Versus Conventional Visual Examination Among a Group of Children: a Diagnostic Accuracy Study

The goal of this observational study is to evaluate the diagnostic accuracy of different deep learning models in detecting dental caries from intra oral images taken by a professional intra oral camera in children. The main question it aims to answer is:

What is the diagnostic accuracy of different deep learning models in detecting dental caries from intra oral images taken by a professional intra oral camera in children compared to the conventional clinical visual examination?

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

398

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Egypt
      • Giza, Egypt
        • Cairo University
        • Contact:
          • mahmoud ahmed Vice President for Graduate Studies and Research, Phd
          • Phone Number: 0235674835 0235674835
          • Email: info@cu.edu.eg
        • Contact:
          • sama sayed hanafy, Phd

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Any child with at least one decayed tooth present at the time of recruitment at the Pediatric dental department diagnostic center, Faculty of Dentistry, Cairo University.

Description

Inclusion Criteria:

  • Child dentition having at least one decayed tooth.

Exclusion Criteria:

  • Child dentition with developmental enamel defects.
  • Children with any systemic medical condition.
  • Parent / child refuse to participate in the study.
  • Uncooperative child.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
training group
images used to train the AI models on detection of dental caries from intraoral images.
Diagnostic test: FASTER RCNN
train artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy
Other Names:
  • YOLO
test group
images used to test the accuracy of the AI models in diagnosis of dental caries from intraoral images.
Diagnostic test: FASTER RCNN
train artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy
Other Names:
  • YOLO

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy Of Dental Caries Detection From Intraoral Images Using Different Artificial Intelligence Models Versus Conventional Visual Examination Among A Group Of Children: A Diagnostic Accuracy Study
Time Frame: one year
Diagnostic accuracy of index tests will be determined, including sensitivity, specificity, overall accuracy, positive and negative predictive values and ROC curve analysis.
one year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Cairo University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 30, 2025

Primary Completion (Estimated)

December 30, 2025

Study Completion (Estimated)

December 30, 2025

Study Registration Dates

First Submitted

December 19, 2024

First Submitted That Met QC Criteria

December 23, 2024

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

February 28, 2025

Last Verified

December 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • OP 7-1-1

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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