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Table 3 Diagnostic performances of the classification models

From: Diagnostic assessment by dynamic contrast-enhanced and diffusion-weighted magnetic resonance in differentiation of breast lesions under different imaging protocols

Classifier

Feature subset

Specificity

Sensitivity

Accuracy

AUC

SVM

Morphology

0.278

0.817

67.74

0.526

Morphology + Texture

0.444

0.851

69.89

0.602

ADC + SER

0.722

0.926

81.72

0.781

Morphology + Kinetic

0.5

0.875

77.42

0.67

Morphology + ADC

0.611

0.903

81.72

0.739

Morphology + Texture + Kinetic

0.556

0.882

75.27

0.678

Entire *%

0.722 30%

0.924 4.8%

79.57 5.7%

0.768 13.3%

KNN

Morphology

0.5

0.85

64.52

0.569

Morphology + Texture

0.444

0.844

66.67

0.619

ADC + SER

0.722

0.917

73.12

0.784

Morphology + Kinetic

0.556

0.867

66.67

0.66

Morphology + ADC

0.611

0.892

74.19

0.794

Morphology + Texture + Kinetic

0.611

0.887

70.97

0.666

Entire *%

0.611 0%

0.899 1.4%

78.49 10.6%

0.744 11.7%

Random Forest

Morphology

0.556

0.871

68.82

0.604

Morphology + Texture

0.667

0.864

53.76

0.609

ADC + SER

0.667

0.9

70.97

0.764

Morphology + Kinetic

0.611

0.885

69.89

0.713

Morphology + ADC

0.667

0.91

78.49

0.8

Morphology + Texture + Kinetic

0.667

0.906

75.27

0.722

Entire *%

0.722 8.3%

0.912 1%

69.89 -7.2%

0.787 9%

Average

Morphology

0.445

0.846

67.03

0.566

Morphology + Texture

0.518

0.853

63.44

0.61

ADC + SER

0.703

0.914

75.27

0.776

Morphology + Kinetic

0.556

0.876

71.33

0.681

Morphology + ADC

0.630

0.873

78.13

0.778

Morphology + Texture + Kinetic

0.611

0.892

73.84

0.689

Entire *%

0.685 12.1%

0.912 2.2%

75.98 2.9%

0.766 11.2%

  1. Remark 1: Entire *%refers to using entire feature set, i.e., Morphology + Texture + Kinetic + ADC, and the subscript *%denotes the increased ratio from Morphology + Texture + Kinetic to Morphology + Texture + Kinetic + ADC.
  2. Diagnostic performances of three classical classification models and their average on different feature subsets. Incorporation of the feature of ADC will dramatically increase the discrimination power of the classification models as well as their average.