a, Example of model attributions for a cancer-positive case. The top row shows the input volume for the full-volume and cancer risk prediction models, respectively. The lower row shows the attribution overlay with positive (magenta) and negative (blue) region contributions to the classifications. In all cancer cases under the attributions study, the readers strongly agreed that the model focused on the nodule. Also, in 86% of these cases, the global and second-stage models focused on the same region. b, Example of model attributions for a cancer-negative case. The left-hand image shows a slice from the input subset volume. The right-hand image image shows positive (magenta) and negative (blue) attributions overlayed. The readers found that, in 40% of the negative cases examined, the model focused on vascular regions in the parenchyma.