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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]