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Table 3 Performance obtained by the proposed methods on the testing set

From: Breast DCE-MRI: lesion classification using dynamic and morphological features by means of a multiple classifier system

Classifier Segmentation Sensitivity (%) Specificity (%) PPV (%) NPV (%) Accuracy (%) p valuea
Bayesian classifier using dynamic features Manual 92.3 (24/26) 81.8 (18/22) 85.7 (24/28) 90.0 (18/20) 87.5 0.04
Automatic 88.5 (23/26) 68.2 (15/22) 76.7 (23/30) 83.3 (15/18) 79.2
Decision tree classifier using morphological features Manual 92.3 (24/26) 77.3 (17/22) 82.8 (24/29) 89.5 (17/19) 85.4 0.02
Automatic 76.9 (20/26) 40.9 (9/22) 60.6 (20/33) 60.0 (9/15) 60.4  
  1. PPV positive predictive value, NPV negative predictive value
  2. aMcNemar test