Table 1

Classification results via cross-validation

Data set

Feature Extraction

AUC

Sensitivity (%)

Specificity (%)

Mf

AVG

STD

AVG

STD


Data1

IR & HE

0.982

0.0030

90

94.76

1.64

13

95

90.91

1.62

99

77.80

5.52


HE only

0.968

0.0052

90

91.64

2.26

11

95

83.90

1.91

99

53.43

13.65


Data2

IR & HE

0.974

0.0145

90

92.53

7.11

7

95

84.19

10.84

99

49.54

22.51


HE only

0.880

0.0175

90

61.34

10.31

8

95

22.21

10.06

99

11.21

6.01


AVG and STD denote average and standard deviation across ten repeats of cross-valdiation. Mf is the median size of the feature set obtained by feature selection from training data. Column "Feature Extraction" indicates if features were obtained using H&E as well as IR data, or with H&E data alone. The parameter γ of a radial basis kernel for SVM is set to 1.

Kwak et al. BMC Cancer 2011 11:62   doi:10.1186/1471-2407-11-62

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