Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models

Table 6 Pairwise comparisons of the models’ overall performances in the training set (P value)

Evaluated metrics	DenseNet121 vs VGG16	DenseNet121 vs ResNet50	DenseNet121 vs ViT	VGG16 vs ResNet50	VGG16 vs ViT	ResNet50 vs ViT
Accuracy	0.004	0.999	0.002	0.006	0.978	0.003
Precision	0.001	0.981	0.003	0.001	0.85	0.001
Recall	0.001	0.995	0.002	0.001	0.212	0.003
F1-score	0.001	0.999	0.001	0.001	0.421	0.001
AU-ROC	0.001	0.984	0.001	0.001	0.304	0.002

VGG: Visual geometry group; ViT: Vision transformer; AU-ROC: Area under the receiver operating curve.