Can training data help radiologists to open deep learning black box?
Deep learning has recently pervaded the radiology field, reaching promising results that have encouraged both scientists and entrepreneurs to apply these models to improve patient care. However, “with great power there must also come — great responsibility” [1]! In most cases, the complexity of deep learning models forces their users, and sometimes also their developers, to treat them as black