KRAS and neoplasm: To explore the associations between multiple clinical features and KRAS mutations, we have employed t-SNE to find the mutational patterns in a particular subgroup sharing three common clinical and histological features, including city, tumor site, histological grade, and then demonstrated that some clinical and histological features hold strong predictive properties for genetic information supported by the validation accuracy at 74.1% in artificial neural network models.