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

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?

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.