Deep Learning For Dual Detection Of Microsatellite Instability And Pole Mutations In Colorectal Cancer Histopathology

This article discusses the use of Deep Learning to predict MSI status from histopathology images in colorectal cancer patients. The model was trained on data from four patient cohorts and achieved a state-of-the-art AUROC of 0.94. The model also showed robust performance on internal data and further external validation is needed.