Abstract This narrative review explores the applications of artificial intelligence (AI) in endodontics, highlighting its transformative impact on diagnostics, treatment planning, and regenerative procedures. AI-driven models enhance the accuracy of root canal anatomy detection, periapical lesion diagnosis, and working length determination. In regenerative endodontics, AI optimizes stem cell classification, scaffold selection, and treatment outcomes. Despite these advancements, limitations such as biased datasets, susceptibility to imaging artifacts, and challenges in clinical integration persist. Future research should focus on expanding datasets, minimizing bias, and addressing ethical and regulatory concerns to fully harness AI’s potential in endodontics.
Mukhopadhyay et al. (Thu,) studied this question.