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Table 2 Classification performance of the individual classifier for region (a), (b), (d), and (e) and the integrated using the selected feature set

From: The development and evaluation of a computerized diagnosis scheme for pneumoconiosis on digital chest radiographs

Lung region

Training dataset

Test dataset

 

AUC

Spe

Sen

Acc

AUC

Spe

Sen

Acc

(a)

0.986

0.832

0.894

0.852

0.879

0.753

0.844

0.786

(b)

0.997

0.996

0.737

0.910

0.939

0.934

0.738

0.866

(d)

0.953

0.811

0.724

0.782

0.835

0.762

0.623

0.711

(e)

0.994

0.971

0.800

0.913

0.889

0.880

0.697

0.817

Integrated

0.997

0.995

0.913

0.969

0.961

0.933

0.849

0.905

  1. AUC = area under ROC curve; Spe = specificity; Sen = sensitivity; Acc = accuracy.
  2. Lung regions (a) and (b) correspond to upper and middle lung field of the right lung, and region (d) and (e) correspond to upper and middle lung field of the left lung, respectively.
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