Explainable artificial intelligence system using a convolutional neural network for designing major connectors of removable partial denture framework

This study demonstrated the feasibility of an AI-based system for predicting RPD major connector types with acceptable performance. The system is expected to provide valuable support to dentists by minimizing the variability owing to differences in clinical skills and experience. Grad-CAM visualization enhances interpretability, enabling both clinicians and patients to better understand the reasoning behind the RPD design process. Ultimately, this approach could improve consistency, efficiency, and training in prosthodontics.