Artificial Intelligence in Pediatric Dentistry: A Systematic Review and Meta-Analysis.

ABSTRACT:

Background/objectives

Artificial intelligence (AI) has gained substantial prominence in pediatric dentistry, offering new opportunities to enhance diagnostic precision and clinical decision-making. AI-based systems are increasingly applied in caries detection, early childhood caries (ECC) risk prediction, tooth development assessment, mesiodens identification, and other key diagnostic tasks. This systematic review and meta-analysis aimed to synthesize evidence on the diagnostic performance of AI models developed specifically for pediatric dental applications.

Methods

A systematic search was conducted in PubMed, Scopus, Web of Science, and Embase following PRISMA-DTA guidelines. Studies evaluating AI-based diagnostic or predictive models in pediatric populations (≤18 years) w

SUBMITTER: Karamuftuoglu N 

PROVIDER: S-EPMC12839933 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature