Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography

Figure 6 Area under the curves for 1-, 2-, and 3-year overall survival prediction using support vector classifier, logistic regression, extra trees classifier, and nomogram models for feature subsets 1 (no-radiomics) and 4 (combined input). ROC: Receiver operating characteristic; AUC: Area under the time-dependent receiver operating characteristic curve.