Accuracy of Detection of Dental Caries from Intraoral Images Using Different ArtificiaI Intelligence Models
- Conditions
- Dental Caries (Diagnosis)Artifical IntelligenceIntraoral Images
- Registration Number
- NCT06749743
- Lead Sponsor
- Cairo University
- Brief 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. 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
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 398
- Child dentition having at least one decayed tooth.
- Child dentition with developmental enamel defects.
- Children with any systemic medical condition.
- Parent / child refuse to participate in the study.
- Uncooperative child.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method 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 one year Diagnostic accuracy of index tests will be determined, including sensitivity, specificity, overall accuracy, positive and negative predictive values and ROC curve analysis.
- Secondary Outcome Measures
Name Time Method
Related Research Topics
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Trial Locations
- Locations (1)
Cairo university
🇪🇬Giza, Egypt