In this experiment, we explored several deep learning base models, including AlexNet, DenseNet-121, EfficientNetV2-S, GoogLeNet, MobileNetV2, ResNet-34, and ShuffleNet, for breast cancer classification using SWE images. These base models were trained on generated SWE images from three public datasets, i.e. BUSI, Breast-Lesions-USG, and BUS-BRA. As a result, the top three models were ResNet-34, MobileNetV2, and GoogLeNet, which can be selected from "modes" list in the tool page.