Teaching Artificial Intelligence Literacy: A Challenge in the Education of Radiology Residents

The growth of cross-sectional imaging (particularly MR and CT) has contributed significantly to increase the workload of radiologists, particularly due to larger datasets to interpret in a shorter amount of time (1). In one institution, the number of cross-sectional images increased tenfold between 1990 and 2010 (2). This has led to increased intra- and inter-observer variability, burnout and diagnostic errors. Against this backdrop, Artificial Intelligence (AI) may turn out to be an attractive partner, one that can help in both interpretive and non-interpretive tasks in radiology (3).