Fig. 5: Pattern recognition allows predicting patient prognosis. | Cell Death & Disease

Fig. 5: Pattern recognition allows predicting patient prognosis.

From: Low expression of pro-apoptotic proteins Bax, Bak and Smac indicates prolonged progression-free survival in chemotherapy-treated metastatic melanoma

Fig. 5

a A principal component analysis was performed on the H scores of nine apoptotic proteins. To provide a visualisation of the spatial clustering, patients samples were positioned in a 3D scatter plot defined by the first three principal components and colour-coded according to their PFS time (red < 12 months, n = 33; blue > 12 months, n = 17). Linear discriminant analysis (LDA) correctly segmented 72% of the patients. Leave One Out Cross Validation (LOOCV) combined with LDA predicted the correct class for 74% of the patients. b 3D scatter plot showing the spatial clustering of patients with short and long PFS based on the H scores for Bax, Bak and Smac. LDA correctly segmented 80% of the patients and LOOCV-LDA achieved 78% prediction accuracy. c Comparison of the performance of the two classifiers shown in a and b. The receiver operating characteristic curves (ROCs) and respective areas under the curve (AUC) are shown.

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