Table 1.

The performance summary of breast ultrasound CAD system.

Reference	Dataset	Features	Classifiers	Performance
[14]	88 benign 90 malignant	Textural features + morphologic features	ANN (BPNN)	Accuracy: 95.86% Sensitivity: 95.14% Specificity: 96.58%
[15]	70 benign 50 malignant	Textural features + morphologic features	SVM	Accuracy: 95.83% Sensitivity: 96% Specificity: 95.71%
[16]	4254 benign 3154 malignant	GoogLeNet		Accuracy: 91.23% Sensitivity: 84.29% Specificity: 96.07%
[17]	135 benign 92 malignant	Boltzmann machine		Accuracy: 93.4% Sensitivity: 88.6% Specificity: 97.1%
[18]	275 benign 245 malignant	Stacked denoising Autoencoder (SDAE)		Accuracy: 82.4% Sensitivity: 78.7% Specificity: 85.7%
[19]	100 benign 100 malignant	Deep polynomial network	SVM	Accuracy: 92.40% Sensitivity: 92.67% Specificity: 91.36%