Shiri et al. [35] reported that the ML model with the stochastic gradient descent algorithm using CT-radiomics and PET-radiomics outperformed conventional methods (peak of standardized uptake value [SUVpeak] or metabolic tumor volume [MTV]) in predicting EGFR and KRAS gene mutation status in NSCLC (EGFR: SUVpeak [AUC: 0.69] vs. ML model [AUC: 0.82]; KRAS: MTV [AUC: 0.55] vs. ML model [AUC: 0.83]). The gene discussed is EGFR; the disease is non-small cell lung carcinoma.