… LASSO regression method was used to select the breast mass classification-… breast tumor
classification with an AUC up to 0.922 (34). A convolutional neural network-based radiomics …

… between benign and malignant breast tumors. Therefore, evidence of … method with CNNs
to discriminate benign and malignant … The results of this study suggest that the CNN model for …

… The CNN architecture does not require manual input of radiomics signatures, but automatically
selects useful features from US images for classification; … for classifying breast cancers via …

… , radiologists have started to use US radiomics to facilitate breast tumour classification [11]. …
In order to validate the robust of the radiomic method, we calculated the BMUS and SWE Rad-…

… Convolutional Neural Network (DCNN) model is applied to US and SWE images and their
combination to classify the breast … The best method of that study is identical to our method …

… Besides, if the extracted features were radiomic parameters, … 4.3, the deep learning model,
particularly CNN in this review, … the elastography review to strain or shear wave elastography, …

… We proposed a deep convolutional neural network by TL to … transient elastography, point
shear wave elastography, and … of the method of a deep convolutional neural network by a …

… radiomics (DLR) of conventional ultrasound and shear wave … in analyzing SWE images on
staging liver fibrosis 22 . … The target breast mass was measured at maximal-diameter plane to …

… All the CNN models combined with radiomics and clinical … as invasive breast carcinoma [2,
3]. SA can also mimic … this improved approach to accomplish intractable classification tasks …

… great potential for classification, especially by utilizing CNN architecture. A … radiomics in
elastography (DLRE) architecture that takes a two-dimensional (2D) shear wave elastography (…