Table 1.

Comparison of existing methodologies.

Paper and Year	Method	Classification	Dataset Used	Accuracy (%)
Al-Baderneh et al. (2012) [18]	NN and KNN	Normal/Abnormal	275 images	100 and 98.92
Rajesh et al. (2013) [14]	Feed Forward Neural Network	Normal/Abnormal	20 images	90
Taie et al. (2017) [15]	SVM		80, 100, and 150 images	90.89 and 100
krishnammal et al. (2019) [24]	AlexNet	Benign/Malignant	Not mention	100
Hanwat et al. (2019) [25]	CNN	Benign/Malignant/ Normal	94 images	71
Hamid et al. (2020) [30]	DWT, GLM, and SVM	Benign/Malignant	Dicom images	95
Kulkarni et al. (2020) [34]	AlexNet	Benign/Malignant	75 Benign and 75 Malignant images	98.44 (F measure)