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Multiple machine learning approaches to identify the best angiogenesis-related prognostic genes in PRAD. (A) Univariate COX regression analysis of prognostic differences in relevant indicators. (B) Multivariate COX regression to analyze prognostic differences in relevant indicators. (C–E) RF, XGBoost and GBM algorithms to screen prognostic genes. (F) Gene enrichment analysis based on MAP7D3 expression.
