developed an end‐to‐end deep learning prediction model, which only needs means to frame the region where the tumor is located, without fine segmentation of the tumor edge, to obtain the EGFR mutation prediction probability of the tumor.[426] Therefore, end‐to‐end learning greatly improves image segmentation accuracy, computational efficiency, and reproducibility in radiogenomics through direct image information transformation of input and output.[427] It is expected to be widely used in medical work in the future to solve current clinical problems. The gene discussed is EGFR; the disease is neoplasm.