Fig. 4 | Scientific Reports

Fig. 4

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

Fig. 4

The correlation between machine learning-derived prognostic signature (MLDPS) and clinical characteristics. (A-C) The correlation between age, gender, grade, IDH status, 1p/19q status and MLDPS in CGGA-693 (A), CGGA-325 (B) and TCGA cohort (C), respectively. (D) Kaplan-Meier survival analysis for overall survival between high and low MLDPS groups in different age, gender, grade, IDH status and 1p/19q status subgroups in CGGA-693 cohort.

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