Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning

Abstract

<i>APC</i>, <i>KRAS</i>, <i>PIK3CA</i>, <i>SMAD4</i>, and <i>TP53</i> mutations can be predicted from H&E pathology images using deep learning-based classifiers, demonstrating the potential for deep learning-based mutation prediction in the CRC tissue slides.