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Fig. 2 | BMC Medical Research Methodology

Fig. 2

From: Dementia risk prediction in individuals with mild cognitive impairment: a comparison of Cox regression and machine learning models

Fig. 2

Distribution of the estimated c-index of nine models, assessed from three-fold CV across 500 replications

NB: There are four panels, with the top two panels (A and B) are for the small samples (based on characteristics and features of PROMPT dataset), the bottom two panels (C and D) are for the large samples (based on characteristics and features of NACC dataset). Left and right panel are for the Cox regression used for data generating process [DGP] and random survival forests [RSF] based DGP, respectively. Each panel consists of nine boxplots corresponding to each of the nine survival analysis models. Each boxplot shows the variation in the Harrell’s c-index [c-index] across the 500 simulation replicates when a certain DGP and survival analysis method were applied. Cox: Cox proportional hazards; Ridge-Cox: Cox regression based on ridge penalty; LASSO-Cox: Cox regression based on Least Absolute Shrinkage Selection Operator penalty; EN-Cox: Cox regression based on elastic net penalty; SurvTree: Survival Tree; RSF: Random survival forests; SSVM: Survival support vector machine; SNN: Survival neural networks; XGBoost: Extreme gradient boosting

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