Even after more than a hundred years after its introduction, histology remains the gold standard in tumor diagnosis and prognosis. Anatomic pathologists evaluate histology to stratify cancer patients into different groups depending on their tumor genotypes and phenotypes, and their clinical outcome [1,2]. However, human evaluation of histological slides is subjective and not repeatable . Furthermore, histological assessment is a time-consuming process that requires highly trained professionals. With significant technological advances in the last decade, techniques such as whole slide imaging (WSI) and deep learning (DL) are now widely available.