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Table 3 Classification results comparing sensitivity, specificity, accuracy, AUC-ROC and error rates for different methods

From: Boosting the diagnostic power of amyloid-β PET using a data-driven spatially informed classifier for decision support

Method

Features

Sensitivity

Specificity

Accuracy

AUC

Error rate

Aβ clusters 1–4, GM voxels and GM SUVR

6

0.83

0.81

0.81

0.91

0.19

Aβ clusters 1–4

4

0.74

0.84

0.80

0.87

0.20

Composite SUVR

1

0.67

0.86

0.79

0.82

0.21

GM voxels and GM SUVR

2

0.44

0.85

0.69

0.71

0.31