Choi et al. [19] used a 3D U-shaped model for glioma segmentation, and then selected 5 images with the largest tumor for each patient based on the segmentation results as the image input of the second model (34-layer Resnet) to predict glioma IDH1 Mutation status. The gene discussed is IDH1; the disease is glioma.