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Table 5 Results in the validation set for the classification of lesions versus normal tissue and malignant versus benign solid lesions using the full texture feature and the reduced feature set

From: Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study

  Predicted
Actual Lesions versus normal tissue (n = 105) Lesions (%) Normal tissue (%)
Lesions (n = 54)
 Full feature set 50 (92.6) 4 (7.4)
 Reduced feature set 52 (96.3) 2 (3.7)
Normal tissue (n = 51)
 Full feature set 3 (5.9) 48 (94.1)
 Reduced feature set 4 (7.8) 47 (92.2)
Malignant versus benign lesions (n = 54) Malignant (%) Benign (%)
Malignant (tot = 27)
 Full feature set 23 (85.2) 4 (14.8)
 Reduced feature set 22 (81.5) 5 (18.5)
Benign (tot = 27)
 Full feature set 1 (3.7) 26 (96.3)
 Reduced feature set 2 (7.4) 25 (92.6)