ABSTRACT Background Artificial intelligence (AI) is increasingly applied in pediatric dentistry for caries detection, risk prediction, anomaly identification, and treatment planning. However, the quality, consistency, and overlap of evidence from existing systematic reviews have not been comprehensively evaluated. Aim To synthesize evidence from systematic reviews on AI in pediatric dentistry, focusing on diagnostic performance, methodological quality, and overlap of primary studies. Methods PubMed/MEDLINE and the Cochrane Database of Systematic Reviews were searched up to 31 August 2025. Methodological quality was assessed using AMSTAR‐2, and overlap was quantified using the corrected covered area (CCA) with the GROOVE tool. Results Seven systematic reviews (109 primary studies) were included—four on early childhood caries, one each on dental anomalies, cleft lip and palate, and caries risk pr
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