Dental Caries (Diagnosis)NCT06749743
Accuracy Of Detection Of Dental Caries From Intraoral Images Using Different ArtificiaI Intelligence Models
An observational study of Dental Caries (Diagnosis) and Artifical Intelligence, run by Cairo University at 1 site in Egypt.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 4 to 12 years
- Conditions the study is for
- Dental Caries (Diagnosis), Artifical Intelligence, Intraoral Images
- What is being tested?
- FASTER RCNN
- How many people
- 398 participants
- Where
- 1 siteEgypt
- Study dates
- 30 Apr 2025to 30 Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 4 to 12 years
- All sexes
- No healthy volunteers
- Child
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.
Who may be able to join
- Child dentition having at least one decayed tooth.
Who cannot join
- Child dentition with developmental enamel defects.
- Children with any systemic medical condition.
- Parent / child refuse to participate in the study.
- Uncooperative child.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Egypt1 site
Cairo university
Giza, Giza Governorate
mahmoud ahmed Vice President for Graduate Studies and Research, Phd, 0235674835 ext. 0235674835, info@cu.edu.eg
sama sayed hanafy, Phd
About this study
Official 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
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?
- Being tested
- FASTER RCNN
- Keywords
- artificial intelligence, dental caries, diagnosis, intraoral images
- Medical subject headings
- Dental Caries, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
FASTER RCNNDiagnostic test
Also called YOLO
train artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy
| Study group | Role | What they receive |
|---|---|---|
| training group | images used to train the AI models on detection of dental caries from intraoral images. Receives: Diagnostic Test: FASTER RCNN | |
| test group | images used to test the accuracy of the AI models in diagnosis of dental caries from intraoral images. Receives: Diagnostic Test: FASTER RCNN |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Diagnostic accuracy of index tests will be determined, including sensitivity, specificity, overall accuracy, positive and negative predictive values and ROC curve analysis.
Measured: one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Dec 2024
- Study start30 Apr 2025 (estimated)
- Primary completion30 Dec 2025 (estimated)
- Study completion30 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Dental Caries (Diagnosis)Studies of the same condition, open and under way.
- More trials run by Cairo UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 398 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Sherine Tarek Mohamed Elsayed Khaled, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06749743
- Sponsor's protocol ID
- OP 7-1-1
- Status last verified
- Dec 2024
- First submitted
- 19 Dec 2024
- Last updated
- 4 Mar 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 4 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official 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
- ClinicalTrials.gov ID
- NCT06749743
- Acronym / sponsor ID
- OP 7-1-1
- Keywords
- artificial intelligence, dental caries, diagnosis, intraoral images
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 398 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 30 Apr 2025 (estimated)
- Primary completion
- 30 Dec 2025 (estimated)
- Study completion
- 30 Dec 2025 (estimated)
- First posted
- 27 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| training group | – | Diagnostic Test: FASTER RCNNimages used to train the AI models on detection of dental caries from intraoral images. |
| test group | – | Diagnostic Test: FASTER RCNNimages used to test the accuracy of the AI models in diagnosis of dental caries from intraoral images. |
Who may qualify
- Ages
- 4 to 12 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
- 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.
Key inclusion criteria (1 listed)
- Child dentition having at least one decayed tooth.
Key exclusion criteria (4 listed)
- Child dentition with developmental enamel defects.
- Children with any systemic medical condition.
- Parent / child refuse to participate in the study.
- Uncooperative child.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| FASTER RCNNAlso: YOLOtrain artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy | Diagnostic test | test group, training group |
Primary outcome
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Mar 2025.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Dental Caries (Diagnosis) and Artifical Intelligence, run by Cairo University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 4 Mar 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Mar 2025.