nnMIL: a generalizable multiple instance learning framework for computational pathology — Stanford

nnMIL is a broadly applicable multiple-instance learning framework connecting patch-level foundation models to robust slide-level clinical predictions that outperforms established methods across tasks for reliable digital pathology.