Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions

Abstract

This review explores the transformative potential of artificial intelligence (AI) in endodontics, focusing on its applications in enhancing diagnostic accuracy, treatment planning, and clinical outcomes. The primary objective is to synthesize current knowledge on AI technologies such as machine learning, deep learning, and neural networks and their integration into endodontic practice. The review methodology involves a critical analysis of existing literature, highlighting advancements in diagnostic imaging, predictive analytics, and procedural assistance. Key findings demonstrate that AI improves the precision of diagnostics, facilitates personalized treatment planning, and supports clinical decision‐making, ultimately enhancing efficiency and patient care. However, challenges such as data privacy issues, algorithmic biases, and integration barriers must be addressed to enable broader adoption. This review concludes that responsible utilization of AI technologies can revolutionize endodontic practice, with future directions emphasizing innovations in augmented reality, robotics, and telehealth to advance patient‐centered care and procedural precision.

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