The effectiveness of endodontic treatment is a complicated interaction of factors and characteristics of patients, teethand the procedure itself. Although the techniques and materials have improved, prognosis prediction is a major clinicalproblem. Artificial intelligence (AI) has become a revolutionary resource in the field of dentistry, as it provides new methodsto improve the accuracy of diagnoses and improve the process of treatment planning. Within the field of endodontics, AIbasedmodels, including machine learning algorithms and deep neural networks are being actively used on the imaging data, electronic health records, and clinical parameters to predict the success or failure of treatment. The predictive systemscan potentially support clinicians to perform early risk analysis, tailor the therapeutic process, and enhance long-termpatient outcomes. Nevertheless, obstacles like heterogeneity of data, ethical issues, and lack of large-scale validation ofstudies prevent mass adoption. The present paper provides a review of the current role of AI in predicting the outcome ofendodontic treatments, its advantages and disadvantages and its future directions by integrating clinically, explaining, andpatient-centric AI systems into endodontic practice.
Sameer Makkar (Wed,) studied this question.