Fig. 3 | Scientific Reports

Fig. 3

From: Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer

Fig. 3

Prognostic value of the risk signature in GC. (A) 3-year and 5-year ROC analysis of TCGA-STAD. (B) 3-year and 5-year ROC analysis of GSE84437. (C) 3-year and 5-year ROC analysis of GES26253. (D) KM survival analysis based on OS in the TCGA-STAD queue. (E) KM survival analysis based on OS in the GSE84437 queue. (F) KM survival analysis based on RFS in GES26253. ROC, receiver operating characteristics; TCGA, The Cancer Genome Atlas; GSE, Gene Set Enrichment; KM, Kaplan-Meier; OS, overall survival; RFS, relapse free survival.

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