Considering that the semantic clinical features like age, sex, smoking history, size, location, the longest diameter (LD) and its longest perpendicular diameter (LPD) of the target lesion, and carcinoembryonic antigen (CEA) are closely related to lung cancer [4, 5], the second aim of this was to investigate whether integrating the radiomics features with these clinical features could further improve the diagnostic performance. Here, CEACAM5 is linked to lung cancer.