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DLRE: For using Radiomics, the enrolled patients were randomly divided into the training cohort and validation (or testing) cohort. One is for training the radiomic model to optimize its parameters, the other is to validate the performance of the generated model. In the training cohort, to reduce the potential bias caused by the unbalanced data for binary classification, a strategy called data augmentation was applied before the training procedure.2D-SWE images in the training cohort were augmented through a number of random transformations, which increased the training data pool and decreased the overfitting of the generated radiomic model. DLRE adopted the CNN method, one of the deep learning radiomic techniques, for the automatic analysis of 2D-SWE images.