Artificial Intelligence in Pediatric Dentistry: A Systematic Review - Click here

This systematic review and meta-analysis investigates the performance of artificial intelligence (AI) technologies in pediatric dentistry. Focusing on diagnostic and predictive applications, the study synthesizes evidence on radiographic caries detection, early childhood caries risk prediction, tooth development assessment, and mesiodens detection. The meta-analysis reports pooled accuracy metrics, highlighting the potential of AI, particularly convolutional neural networks (CNN), to enhance clinical decision-making. The review also identifies limitations, including heterogeneity of datasets, lack of external validation, and ethical considerations. Key recommendations for future research include large multicenter datasets, standardized annotation protocols, and explainable AI models to facilitate safe integration into pediatric dental practice.