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Table 3 Performance of individual DLMs for contrast-enhancement classification: comparison among the algorithm models in each body part

From: Development and validation of an ensemble artificial intelligence model for comprehensive imaging quality check to classify body parts and contrast enhancement

Body part

Preprocessing

Internal validation set

External validation set

Precision (%)

Recall (%)

Accuracy (%)

F1-score (%)

Precision (%)

Recall (%)

Accuracy (%)

F1-score (%)

Brain

Mid-axial

100

100

100

100

100

100

100

100

Neck

100

100

100

100

98.38

98.33

98.33

98.3

Chest

100

100

100

100

98.38

98.48

98.41

98.4

Abdomen

100

100

100

100

100

100

100

100

Abdomen and pelvis

100

100

100

100

97.78

97.87

98.34

97.9

Brain

Mid-sagittal

100

100

100

100

99.13

98.33

98.85

98.7

Neck

100

100

100

100

84.09

76.66

76.66

80

Chest

100

100

100

100

100

100

100

100

Abdomen

100

100

100

100

100

100

100

100

Abdomen and pelvis

100

100

100

100

100

100

100

100

Brain

Mid-coronal

100

100

100

100

99.13

98.33

98.85

98.7

Neck

100

100

100

100

91.17

91.66

91.66

91.4

Chest

100

100

100

100

100

100

100

100

Abdomen

100

100

100

100

100

100

100

100

Abdomen and pelvis

100

100

100

100

100

100

100

100