Abstract 1632: Deep learning functional associations using histopathology images

Histopathological images have critical value for understanding cancer subtype, local structure, and malignancy. Manual interpretation of such images can be time-consuming and error-prone, while also failing to make use of the power of image aggregation for coordinated data mining. Large-scale patient cohorts such as TCGA provide high-resolution HE 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1632.