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Table 7 Output comparison between final model, OR (Original Reader), and OOBTR (Out Of Box Test Reader). Model output compared with OOBTR and OR using multiple evaluation metrics for multiple binary classifications with binary output classes derived from the original multiclass output values

From: A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays

 

O.O.B.T.R.- O.R.

Model- O.R.

Model- O.O.B.T.R.

Absence or Presence of Opacity

 Precision

92.50

88.64

88.89

 Recall

89.53

91.19

93.62

 F1

90.95

89.89

91.12

 R-squared

0.45

0.42

0.49

No Opacity, Mild Opacity VS. Medium & Severe Opacity

 Precision

77.53

81.31

82.57

 Recall

75.08

84.23

84.08

 F1

76.25

82.51

83.01

 R-squared

0.21

0.44

0.46

Not Severe or Severe

 Precision

46.64

55.27

71.56

 Recall

62.57

80.64

69.53

 F1

53.45

65.45

70.32

 R-squared

0.06

0.02

0.28