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Fig. 4 | Journal of Translational Medicine

Fig. 4

From: An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy

Fig. 4

Evaluation of nomogram integrated RIS and clinical pathological variables in the training cohort. A Nomogram for predicting the ratio of GC patients with a certain survival time in the training cohort; Calibration plots describing the calibration of nomogram based on the consistency between predicted and observed 1-year (B), 3-year (C) and 5-year (D) results; E Decision curves comparing the nomogram and TNM stage among a series of risk thresholds; F Risk factor association diagram showing the distribution of prognosis of each patient with high- or low-nomogram scores; G, J Time-independent ROC curves comparing the predictive accuracy of nomogram and TNM stage; H, K Time-dependent ROC curves comparing the predictive accuracy of nomogram and TNM stage; I, L Kaplan–Meier analysis of overall survival curves of High- and Low-nomogram in training group and validation group

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