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Table 2 Optimal levels of performance using ROC curves

From: The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation

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t ROC

Probability

Sensitivity

Specificity

Precision

Accuracy

F

Youden

Matthews

BCI

0.606

0.534

0.980

0.941

0.941

0.960

0.960

0.921

0.9208

Daylight

0.510

0.225

1.000

0.882

0.891

0.940

0.942

0.882

0.8866

ECFP4

0.490

0.406

0.980

0.922

0.923

0.950

0.951

0.901

0.9017

ECFC4

0.364

0.415

0.980

0.882

0.889

0.930

0.932

0.862

0.8645

MDL

0.650

0.487

0.939

0.882

0.885

0.910

0.911

0.821

0.8216

Unity

0.639

0.537

0.938

0.961

0.957

0.950

0.947

0.898

0.8990

  1. t ROC is the similarity threshold that gives the best level of performance, where this is that similarity value which maximises the values of the precision, the accuracy, the F index, the Youden index and the Matthews coefficient whilst maintaining acceptable values of the sensitivity and specificity. The largest values of these last five variables are bold-faced in the table.