An explainable and transparent machine learning approach for predicting dental caries: a cross-national validation study

Key Points

• The aim is to evaluate the performance of a machine learning model for predicting dental caries risk using explainable AI approaches.
• Conducted internal and external validation of a machine learning model.
• Applied explainable artificial intelligence techniques for insights.
• Compared model performance across different populations.
• The model's performance significantly declined during external validation compared to internal validation.
• The XAI methodology showed promise for personalized risk assessment of dental caries.