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Fig. 2 | BMC Medical Research Methodology

Fig. 2

From: Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis

Fig. 2

Comparison of Discrimination for Sudden Cardiac Arrest (SCA) Prediction with Different Random Forests Approaches. a, b, c Time-varying AUC curves for the RSF approach which uses only baseline covariates (panel a), RF-SLAM approach with only baseline covariates (panel b), RF-SLAM approach with both baseline and time-varying covariates (panel c). d, e, f Predicted survival curves from RSF (panel d), RF-SLAM approach with only baseline covariates (panel e), and RF-SLAM approach with both baseline and time-varying covariates (panel f). Individuals who experienced an SCA are colored-coded in red and all others are colored-coded in green. Note each column of plots corresponds to the same model (i.e. the left column corresponds to the RSF approach, center column corresponds to the RF-SLAM approach with only baseline covariate, and the right column corresponds to the RF-SLAM approach with both baseline and time-varying covariates)

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BMC Medical Research Methodology

ISSN: 1471-2288

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