This systematic review and meta-analysis assesses the accuracy of artificial intelligence (AI) platforms in detecting dental caries using clinical images and radiographs. The researchers conducted a comprehensive search of eight databases, identifying 45 studies for qualitative synthesis and seven for meta-analysis. The meta-analysis revealed a mean sensitivity of 76% and specificity of 91% for AI-based caries detection, although significant heterogeneity existed across studies. The authors highlight substantial variations in AI performance, data quality, and methodological approaches, emphasizing the need for standardization and further research to improve the reliability and consistency of AI in dental caries diagnosis. The study concludes that while AI shows promise, further refinement is crucial before it can replace traditional diagnostic methods.

Lyndon P Abbott ,Ankita Saikia , Robert Anthonappa , Artificial Intelligence Platforms in Dental Caries Detection: A Systematic Review and Meta-Analysis,The Journal of Evidence-Based Dental Practice (2024), doi: https://doi.org/10.1016/j.jebdp.2024.102077