Comparative Accuracy of AI Models and Clinical Assessment for Dental Plaque Detection in Children
ConditionDental Plaque
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age7-12
SponsorNaema Ahmed
About this trial
This diagnostic accuracy study aims to evaluate the effectiveness of various artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments performed by dentists among children. The study seeks to determine the accuracy, sensitivity, specificity, and overall performance of AI technologies in identifying dental plaque. study study Design: Observational study
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
None
Disqualifiers
Children with developmental enamel defects
Children who are unwilling to cooperate or who has mental retardation and are prohibited from having their images taken. .Children who's their legal guardians will not approve to participate in the study.
Trial population
Children from 7 to 12 years old.
Trial design
Design model
Other
Time perspective
Prospective
Treatments tested in this trial
Dental Plaque Detection Using AI Models
Diagnostic test1. AI Model Analysis: Description: Intraoral images of participants will be captured using standardized imaging techniques. These images will then be analyzed using various artificial intelligence models specifically designed for detecting dental plaque. The AI models will process the images to identify and quantify the presence of dental plaque. 2. Clinical Assessment: Description: A qualified dentist will perform a traditional clinical examination of the participants to assess dental plaque using standard examination techniques. This will serve as the reference standard against which the AI models will be compared. Study Procedures Image Acquisition: Intraoral images will be taken of each participant using \[ intraoral camera\]. AI Model Evaluation: The captured images will be analyzed using different AI algorithms, which may include.
Treatment groups
323 Participants
are divided into 2 treatment groupsGroup A: intraoral images for Children with Dental Plaque for assessment by dentist0 interventions
Group B: intraoral images for Children with Dental Plaque for assessment by AI models1 intervention
Trial outcomes
Primary outcomes
1
accuracy of dental plaque detection
The primary outcome measure evaluates the diagnostic accuracy of different artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments.
Time frame
primary outcome will be assessed at Baseline Prior to any intervention, intraoral images will be captured and assessed using AI models and clinical evaluation.Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Naema Ahmed
Lead sponsor
Cairo University
Sponsor institution
Source ClinicalTrials.gov
This trial is not recruiting at the moment. You can still explore other options: