Application of Artificial Intelligence in Radiological Exams as a Medical Education Tool: A Scoping Review Protocol

This study consists of a scoping review aimed at mapping and analyzing the use of Artificial Intelligence in radiology as a tool for medical education. The review seeks to identify the main strategies for using Artificial Intelligence in radiology teaching during medical training, as well as to recognize gaps related to its absence or limited integration into traditional educational models. The review will be conducted in accordance with the methodological guidelines of the Joanna Briggs Institute (JBI) for scoping reviews. The reporting of results will follow the recommendations of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses – Scoping Review Extension). Studies published within the last five years, available in full text, in Portuguese, English, and Spanish, will be included. Searches will be performed in the following databases: PubMed, LILACS, Cochrane Library, Scopus, and Web of Science. The temporal scope was defined considering the rapid technological advancement of Artificial Intelligence in healthcare and medical education, particularly following recent developments in machine learning and generative AI from 2021 onward, aiming to capture the most current and relevant evidence. As this review follows JBI methodological guidance for scoping reviews, a formal risk of bias assessment will not be conducted, since the objective of this study is to map the available evidence rather than assess effectiveness.