Table 3 Predictive model building results.

	Model ID	AUC	Accuracy	Precision	Recall	F1 score	Inputting methods	Screening methods	Models
FBG	Model 1	0.819	0.7439	0.7733	0.6901	0.7293	Modified random forest inputting	Not	Ensemble learning
	Model 2	0.8163	0.7423	0.7674	0.6955	0.7297	Modified random forest inputting	Not	XGBoost
	Model 3	0.8119	0.7415	0.7692	0.69	0.7275	Modified random forest inputting	Boruta	Ensemble learning
	Model 4	0.8087	0.7404	0.769	0.6872	0.7258	Modified random forest inputting	Lasso	Ensemble learning
	Model 5	0.8082	0.7388	0.7629	0.6929	0.7262	Modified random forest inputting	Boruta	XGBoost
HbA1c	Model 1	0.9704	0.9217	0.894	0.9463	0.9194	Modified random forest inputting	Boruta	Ensemble learning
	Model 2	0.9702	0.924	0.9135	0.9268	0.9201	Modified random forest inputting	Not	Ensemble learning
	Model 3	0.9697	0.924	0.9095	0.9317	0.9205	Modified random forest inputting	Lasso	Ensemble learning
	Model 4	0.9688	0.9263	0.9179	0.9268	0.9223	Modified random forest inputting	Lasso	XGBoost
	Model 5	0.9674	0.9171	0.9043	0.922	0.913	Modified random forest inputting	Not	XGBoost

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