Fig. 6From: Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methodsPrognostic model construction and efficiency assessment. a, b Visualization of the risk score and survival for each patient in the training set. c The heat map comparing the PSI levels of the 16-ASE signature in the high-risk and the low-risk group of the training set. d Kaplan–Meier survival curve for patients in the high-risk and the low-risk group of the training set. e Time-dependent ROC curves for LUAD patients in the training set. f, g Visualization of the risk score and survival for each patient in the test set. h The heat map comparing the PSI levels of the 16-ASE signature in the high-risk and the low-risk group of the test set. i Kaplan–Meier survival curve for patients in the high-risk and the low-risk group of the test set. g Time-dependent ROC curves for LUAD patients in the test setBack to article page