Comparative Accuracy of AI Models and Clinical Assessment for Dental Plaque Detection in Children

Condition(s) studied

Investigational drug(s) / intervention(s)

Dental Plaque Detection Using AI Models: 1. 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.

Study summary

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

Primary outcome measure(s)

• accuracy of dental plaque detection — primary outcome will be assessed at Baseline Prior to any intervention, intraoral images will be captured and assessed using AI models and clinical evaluation.
  The primary outcome measure evaluates the diagnostic accuracy of different artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments.

Trial sites (1)