analyzed PET or CT images using a 2D small residual convolutional network model, which can predict the EGFR mutation status of NSCLC (AUC = 0.86) and guide patients in making treatment decisions.[110] Similar studies also believe that the combination of PET radiomics can significantly improve the prediction ability relative to conventional PET parameters.[395] Similar to EGFR, the relationship between KRAS mutation and conventional PET parameters has also produced conflicting results,[131, 396] but radiomics using PET can also predict KRAS mutation.[131, 397] Kong et al. This evidence concerns the gene KRAS and non-small cell lung carcinoma.