AI is shifting oral healthcare from a hardware-centric to a software-centric approach, with the potential to solve problems similarly to humans. It is transforming endodontics by enhancing diagnostic accuracy, improving treatment planning, increasing clinical efficiency, and supporting personalized care. This review explores AI applications in endodontics, including working length determination, periapical and caries detection, complex root anatomy segmentation, vertical root fracture identification, and surgical planning. AI models such as convolutional neural networks and artificial neural networks demonstrate high accuracy in interpreting CBCT and radiographic data. Benefits include improved workflow efficiency, reduced misdiagnoses, and individualized treatment strategies. However, challenges remain, such as limited high-quality datasets, regulatory gaps, and ethical considerations. Future directions emphasize technological advancements, collaborative AI-clinician integration, and AI-driven education and training tools. AI stands as a transformative force in endodontics, requiring responsible implementation and continued research to optimize its impact on patient care and clinical practice.
Mukhtiar et al. (Thu,) studied this question.
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