A study by Jiang at al. [35] in a larger cohort of 399 patients with stage I–IV non-small cell lung cancer assessed ML models from CT-, PET-, and combined PET/CT-derived features to predict PD-L1 assessment, showing that CT-derived features achieved the highest predicting efficacy in discriminating PD-L1 expression level higher than either 1% or 50%. The gene discussed is CD274; the disease is non-small cell lung carcinoma.