Machine learning and radiomics differentiate Crohn’s disease and ulcerative colitis
This retrospective study investigated whether volumetric visceral adipose tissue (VAT) features that were extracted using radiomics and three-dimensional convolutional neural network (3D-CNN) approaches are effective when differentiating Crohn’s disease (CD) and ulcerative colitis (UC). The authors concluded that VAT-based deep learning and radiomics features were able to achieve fair accuracy in differentiating CD from UC. Key points High-output feature data