AI-Based Detection of Dental Caries in Children

Condition(s) studied

Study summary

This study aims to evaluate the effects of an artificial intelligence (AI)-based caries detection system on the diagnosis and categorization of dental caries in pediatric patients. The purpose of this research is to better understand how AI may help improve the accuracy and reliability of early dental caries detection compared to traditional clinical examination methods. Participants in this study will be pediatric patients aged 6-9 years, and they will undergo clinical evaluations for dental caries. The study will compare the AI system's performance to conventional clinical examination in terms of sensitivity, specificity, and overall diagnostic accuracy. The progress of participants will be monitored over a period of six months, with regular assessments of their caries detection results. The study will assess the effectiveness, reproducibility, and diagnostic accuracy of the AI model. Throughout the study, participants will be closely monitored by dental healthcare providers to ensure their safety and well-being. Participants and their guardians are encouraged to communicate any concerns or questions with the study team.

Eligibility

Primary outcome measure(s)

• Diagnostic accuracy of the AI model — Within 6 months of enrollment
  Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the AI-based model in detecting dental caries in pediatric patients.

Trial sites (1)

Other trials for the same condition