Fig. 2 | Scientific Reports

Fig. 2

From: Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma

Fig. 2

Construction of the machine learning-derived prognostic signature (MLDPS). (A) The C-index of 65 machine learning algorithms combinations in CGGA-693 training procedure. (B) The C-index of 65 machine learning algorithms combinations in CGGA-325 training procedure. (C) The C-index of 65 machine learning algorithms combinations in TCGA training procedure. (D-F) Top five average C-index in CGGA-693, CGGA-325 and TCGA training procedure, respectively. (G-I) The performance of MLDPS was compared with common clinical and molecular characteristics in CGGA-693 (G), CGGA-325 (H) and TCGA (I). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

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