The use of artificial intelligence (AI) in mammography interpretation has been widely discussed in recent years. Traditional computer-aided detection (CAD) systems, introduced in the 1990 s, were initially expected to reduce diagnostic errors, but their high false-positive rates and limited ability to improve cancer detection accuracy led to mixed results [1–3]. However, the advent of deep learning-based AI systems has changed this narrative. Recent studies have shown that AI, when applied to ma…