Accuracy Of Detection Of Dental Caries From Intraoral Images Using Different ArtificiaI Intelligence Models
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age4-12
SponsorCairo University
About this trial
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?
Eligibility criteria
Qualifiers
Child dentition having at least one decayed tooth.
Disqualifiers
Child dentition with developmental enamel defects.
Children with any systemic medical condition.
Parent / child refuse to participate in the study.
Uncooperative child.
Trial design
Treatments tested in this trial
- FASTER RCNN
Treatment groups
398 Participants
are divided into 2 treatment groupsSponsors and collaborators
Source ClinicalTrials.gov