Artificial Intelligence-Driven Approaches in Prosthodontic Treatment Planning: A Review

Abstract

Artificial intelligence (AI) is transforming prosthodontic treatment planning by enhancing diagnostic accuracy, treatment precision, and patient-specific customisation. The study aims to review the artificial intelligence-driven approaches in prosthodontic treatment planning. By integrating large datasets from digital impressions, radiographs, CBCT scans, and functional assessments, AI facilitates comprehensive analysis, automated prosthesis design, predictive outcome modelling, and real-time monitoring. Deep learning models, including convolutional neural networks (CNNs) and generative algorithms, improve image-based diagnostics, margin detection, occlusal analysis, and personalised prosthetic fabrication through CAD/CAM workflows. AI also optimises implant planning, surgical simulation, and risk assessment, increasing procedural accuracy and long-term success rates. While AI reduces human error, standardises decision-making, and streamlines clinical workflows, challenges such as high implementation costs, data limitations, ethical considerations, clinician acceptance, and regulatory hurdles remain. Future integration with augmented and virtual reality, continuous learning systems, and fully automated treatment planning holds promise for highly precise, efficient, and patient-centred prosthodontic care. Ultimately, AI paves the way for fully automated, predictive, and highly personalized prosthodontic workflows in the future.