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

NCT ID: NCT06749743

Last Updated: 2025-03-04

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

398 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-04-30

Study Completion Date

2025-12-30

Brief Summary

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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?

Detailed Description

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Conditions

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Dental Caries (Diagnosis) Artifical Intelligence Intraoral Images

Study Design

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Observational Model Type

OTHER

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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training group

images used to train the AI models on detection of dental caries from intraoral images.

FASTER RCNN

Intervention Type DIAGNOSTIC_TEST

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

test group

images used to test the accuracy of the AI models in diagnosis of dental caries from intraoral images.

FASTER RCNN

Intervention Type DIAGNOSTIC_TEST

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

Interventions

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FASTER RCNN

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

Intervention Type DIAGNOSTIC_TEST

Other Intervention Names

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YOLO

Eligibility Criteria

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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.
Minimum Eligible Age

4 Years

Maximum Eligible Age

12 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Cairo University

OTHER

Sponsor Role lead

Responsible Party

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Sherine Tarek Mohamed Elsayed Khaled

principal investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Cairo university

Giza, Giza Governorate, Egypt

Site Status

Countries

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Egypt

Facility Contacts

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mahmoud ahmed Vice President for Graduate Studies and Research, Phd

Role: primary

0235674835 ext. 0235674835

Other Identifiers

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OP 7-1-1

Identifier Type: -

Identifier Source: org_study_id

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