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Table 6 Comparison of our kernel-based integration approach with the ensemble approach

From: A kernel-based integration of genome-wide data for clinical decision support

Outcome AUC (SE)*:MPT1/MG AUC (SE)*: ensemble approach p-value
WHEELER 0.9269 (0.0425) 0.9500 (0.0339) 0.6160
pN-STAGE 0.9870 (0.0135) 0.9253 (0.0432) 0.1422
CRM 0.9630 (0.0344) 0.7860 (0.0783) 0.0384
GRADE 0.9006 (0.0413) 0.8567 (0.0521) 0.3745
STAGE 0.8528 (0.0550) 0.8304 (0.0582) 0.6836
METASTASIS 0.9868 (0.0121) 0.9452 (0.0309) 0.1313
RECURRENCE 0.7857 (0.0934) 0.4545 (0.1352) 0.0182
  1. *Area under the ROC curve (standard error) obtained with leave-one-out. Comparison in AUC between the best models obtained with our strategy (MPT1 for rectal cancer, MG for prostate cancer) and the corresponding ensemble models based on the same number of features [46]