To further evaluate the prognostic value of ASCC3 in combination with six immune-related genes (JAK1, NFKB1, SEMA5A, NR2C2, CNTF and CREB1) for rectal cancer patients, we constructed diagnostic and prognostic models using various machine learning algorithms (Figure 7A), including Generalized Linear Model (GLM), Random Forest (RF), Elastic Net, K-Nearest Neighbors (KNN), Stepwise Linear Discriminant Analysis (stepLDA), Logistic Regression (Logit), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Naive Bayes (NaiveBayes), and Partial Least Squares (PLS). The gene discussed is CREB1; the disease is rectal cancer.