Roles of biochemistry data, lifestyle, and inflammation in identifying abnormal renal function in old Chinese

Figure 1 Flowchart of sample selection from the MJ chronic kidney disease study cohort.

Figure 2 Area under receiver operating characteristic curve derived from five different machine learning methods in different models. A: Model 1; B: Model 2; C: Model 3. MARS: Multivariate adaptive regression splines; XGBoost: eXtreme Gradient Boosting; SGB: Stochastic gradient boosting; LightGBM: Light Gradient Boosting Machine; CATboost: Categorical Features + Gradient Boosting. Model 1: Demographic and biochemistry data; Model 2: Model 1 + lifestyle factors; Model 3: Model 2 + inflammation factors.

Figure 3 Averaged ranks of importance for each risk factor in three different models. Model 1: Demographic and biochemistry data; Model 2: Model 1 + lifestyle factors; Model 3: Model 2 + inflammation factors.