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Gene expression data are chosen, normalized, and z-score transformed. A K-fold cross-validation is used for the development of the random survival forest (RSF) prognosis model (K = 5). The 9-genes signature was selected to develop the RSF prognosis model. A fully-developed model based on the optimal parameters identified in cross-validation was then evaluated in an independent dataset.
