ColoRectalCADx: Expeditious Recognition of Colorectal Cancer with Integrated Convolutional Neural Networks and Visual Explanations Using Mixed Dataset Evidence

Table 14

Comparison of the results of previous state-of-the-art methods from 2021 to 2022.

Dataset	Author	Method	Accuracy in %
CVC Clinic DB	Attallah and Sharkas [17]	GastroCADx	—
	Liew et al. [62]	Ensemble classifier (ResNet50+AdaBoost)	97.91
	Sharma et al. [10]	Ensemble classifier	98.3
	Nisha et al. [63]	DP-CNN	99.6
	Souaidi and El Ansari [64]	MP-FSSD	91.56
	Ours	ColoRectalCADx(previous)	99
Kvasir2	Attallah and Sharkas [17]	GastroCADx	97.3
	Sharma et al. [10]	Ensemble classifier	97
	Ours	ColoRectalCADx (previous)	88
Hyper Kvasir	Attallah and Sharkas [17]	GastroCADx	99.7
	Ours	ColoRectalCADx (previous)	84
Mixed dataset	Ours	ColoRectalCADx (proposed)	84.7