Thus, a total of 16 clinical characteristics, including N-terminal pro-B-type natriuretic peptide (NT-proBNP), CD4+T cell, lymphocyte, C-reactive protein (CRP), positive serum (1,3)-β-D-glucan test (G test), serum sodium, ratio of arterial oxygen partial pressure (mmHg) to fractional inspired oxygen (PF ratio), neutrophil, heart rate (HR), chronic obstructive pulmonary disease (COPD), serum glucose, pH, high density lipoprotein cholesterol (HDL-C), albumin, platelet and confusion, were served as predictors to establish machine learning-based prediction models (Fig. 2E). The gene discussed is CRP; the disease is chronic obstructive pulmonary disease.