Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images

Abstract

Histopathological images are a rich but incompletely explored data type for studying cancer. Here the authors show that convolutional neural networks can be systematically applied across cancer types, enabling comparisons to reveal shared spatial behaviors.