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Accuracy Of Detection Of Dental Caries From Intraoral Images Using Different ArtificiaI Intelligence Models
Sponsor: Cairo University
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?
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
Key Details
Gender
All
Age Range
4 Years - 12 Years
Study Type
OBSERVATIONAL
Enrollment
398
Start Date
2025-04-30
Completion Date
2025-12-30
Last Updated
2025-03-04
Healthy Volunteers
No
Interventions
FASTER RCNN
train artificial intelligence models ( FASTER RCNN, YOLOY ) to detect dental caries , then test their accuracy
Locations (1)
Cairo university
Giza, Giza Governorate, Egypt