Aim and background: Artificial intelligence (AI) is revolutionizing endodontics by enhancing diagnostic accuracy, treatment planning, and clinical decision-making.This review explores AI applications in endodontic imaging, working length determination, root canal morphology assessment, and treatment outcome prediction.Methods: A literature review was conducted to evaluate AI models, including convolutional neural networks and machine learning algorithms, in endodontics.Studies comparing AI-assisted and conventional diagnostic methods were analyzed for efficacy and reliability.Results: Artificial intelligence has demonstrated high accuracy in detecting periapical lesions, with sensitivity and specificity comparable to experienced endodontists.Artificial intelligence-assisted cone-beam computed tomography imaging improves the identification of complex root morphologies, such as calcified and missed canals.Predictive models enhance treatment outcome assessment, reducing variability in clinical decision-making.Artificial intelligence-integrated digital workflows optimize patient management and procedural efficiency.Conclusion: Artificial intelligence has the potential to transform endodontic diagnosis and treatment, improving precision and efficiency.While promising, challenges related to data standardization, ethical considerations, and clinical validation must be addressed.Advancements in AI-driven robotics and decision support systems may further refine endodontic procedures.
A Fri, study studied this question.