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Table 4 Performance comparison with our model and Elastic Net model

From: Prediction of prognostic signatures in triple-negative breast cancer based on the differential expression analysis via NanoString nCounter immune panel

Model aAUC bPPV
cpCR model 0.84 0.7
d RELAPSE model 0.88 0.69
EEN pCR model 0.64 0
fEN RELAPSE model 0.68 0.23
  1. aAUC: Receiver Operating Characteristic Area Under Curve
  2. bPPV: Predictive Positive Value (TP / TP + FP)
  3. cOur model pCR: Random Forest analysis using pCR DEG.
  4. dOur model RELAPSE: Random Forest analysis using RELAPSE DEG.
  5. eEN model pCR: Random Forest analysis using EN pCR genes (alpha value < 0.95)
  6. fEN model RELAPSE: Random Forest analysis using EN RELAPSE genes (alpha value < 0.2)
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