Accuracy Of Detection Of Dental Caries From Intraoral Images Using Different ArtificiaI Intelligence Models

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?

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Key information

Conditions

Dental Caries (Diagnosis) Artifical Intelligence Dental Caries Disease Intraoral Images Pathologic Processes Pathological Conditions, Signs and Symptoms Stomatognathic Diseases Tooth Demineralization Tooth Diseases

Age range

4 year–12 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Cairo university

Giza, Giza Governorate, Egypt

Location contact

mahmoud ahmed Vice President for Graduate Studies and Research, Phd

CONTACT

[email protected]

0235674835 ext. 0235674835

sama sayed hanafy, Phd

SUB_INVESTIGATOR

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

FASTER RCNN

Diagnostic Test

train artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy

Other names: YOLO

Primary outcomes

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.

Sponsors and collaborators

Lead sponsor

Cairo University

Other

Registry information

Official study title

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

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: Dec 27, 2024
Registry last updated: Mar 4, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

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