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Table 2 Classification results with the binary classifier of Pain2D for each rare disease versus CP, listing values for true positives (TP), false positives (FP), true negatives (TN), false negatives (FN), p value (Fisher’s exact test), accuracy (Acc), sensitivity (Sens), specificity (Spec), AUC of the ROC curve (AUCROC)

From: A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D

 

TP

FP

FN

TN

p value

Acc

Sens

Spec

AUCROC

EDS versus CP

58

35

1

15

< 0.001

0.67

0.98

0.30

0.899 (CI 0.892–0.954)

GBS versus CP

28

17

1

33

< 0.001

0.77

0.96

0.66

0.921 (CI 0.853–0.973)

FSHD versus CP

34

32

1

18

< 0.001

0.61

0.97

0.36

0.854 (CI 0.77–0.93)

PROMM versus CP

80

24

9

26

< 0.001

0.76

0.90

0.52

0.846 (CI 0.774–0.908)

  1. In all cases, the p values (Fisher’s exact test) suggest strongly that the classifier performs much better than random guessing
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Orphanet Journal of Rare Diseases

ISSN: 1750-1172