Six feature genes (AADAT, APOF, GPC3, LPA, MASP1, and NAT2) were identified using machine learning algorithms such as Random Forest, support vector machine-recursive feature elimination [9,16], and one more study similar to the four-gene model was developed for diagnosing sepsis/severe acute respiratory distress syndrome (ARDS), demonstrating high diagnostic and predictive performance through calibration curves and decision curve analyses [8,9,17]. The gene discussed is NAT2; the disease is Sepsis.