Researchers in China developed an explainable deep learning model that analyzes contrast-enhanced CT scans to predict whether non-muscle-invasive bladder cancer will recur within two years after surgery. The work targets decision support in recurrence risk stratification by using interpretability techniques to connect imaging features to predicted outcomes.