ACE2 and COVID-19: Our main findings are that our framework can: i) encode ACE2-RGF imaging biomarkers using LUAD data, which are distinct to radiomics features extracted for COVID-19 classification and critical illness identification; ii) the ACE2-RGF can distinguish COVID-19 from normal subjects, and can be combined with COVID-19 RF to improve classification performance; iii) the ACE2-RGF can also effectively identify COVID-19 patients with critical illness and, iv) the ACE2-RGF can be used as a biomarker for various applications, as shown for both COVID-19 classification and critical illness identification.