Artificial intelligence in endodontics: a systematic review

Background: In recent years, Artificial Intelligence (AI) has emerged as a transformative force across various healthcare domains, offering innovative tools to support clinical decision-making and improve patient outcomes. In dentistry, especially in endodontics, AI is gaining increasing attention for its ability to enhance diagnostic precision and streamline therapeutic workflows. Endodontic procedures often require high-resolution imaging and accurate interpretation of complex anatomical structures. Empowered by machine learning and deep learning algorithms, AI can analyse large datasets derived from radiographic sources, such as Cone Beam Computed Tomography (CBCT), periapical intraoral radiographs, and panoramic images, with the potential to assist in detecting root canal calcifications, segmenting periapical lesions, assessing treatment quality, and predicting prognosis. Despite promising preliminary findings, a systematic evaluation of AI’s practical applications and performance in endodontics is needed to understand its true clinical value and future integration into routine practice. Conclusions: Artificial Intelligence (AI) demonstrates strong potential in endodontics, offering diagnostic accuracy comparable to that of expert clinicians and enabling personalized treatment planning through advanced image analysis. Its potential extends to education, supporting students and practitioners in interpreting complex cases. Nonetheless, widespread adoption remains limited by challenges such as the need for robust datasets, technical and financial demands, and the predominance of retrospective studies. Future research should focus on prospective validation, improved model transparency, and ethical integration to fully realize AI’s potential to enhance clinical outcomes.