Artificial Intelligence (AI), defined as systems capable of replicating human tasks aimed at performing complex tasks and supporting decision-making, is entering the field of Dentistry, standing out with its application in research and clinical practices, such as diagnosis using Cone Beam Computed Tomography. The objective of this study is to identify and organize scientific evidence related to the use of Artificial Intelligence in computed tomography as an advanced resource in Endodontics. This study is an integrative review, structured in well-defined steps, namely: formulation of the guiding question, selection of inclusion and exclusion criteria, identification of descriptors for creating the search strategy in English and Portuguese, and selection of databases Scopus, Web of Science, PubMed, LILACS, and Google Scholar. Articles addressing the application of Artificial Intelligence in Computed Tomography in Endodontics were included, without distinction of ethnicity and/or sex of patients. Duplicates and content unrelated to the core topic were excluded. A total of 20 articles were included for full analysis and reading. The analysis highlights the variety of benefits, objectives, artificial intelligence models, individualities in tomography categories used, and a plurality of study limitations presented in the articles. The application of Artificial Intelligence (Al) in the analysis of tomographic images in Endodontics show great potential for use for patient diagnosis and therapeutic planning.
Fagundes et al. (Sat,) studied this question.