KRAS and colorectal cancer: Deep learning models are particularly good at feature extraction, and they can capture individual morphological features, such as nuclear atypia or tissue architectural abnormalities that can predict not just the occurrence of malignancies but also possible mutations, such as IDH1 (in glioma) or KRAS (in colorectal cancer) [151].