Table 1.

AUC values tabulated for various machine learning methods on test set of T2D and Cirrhosis studies

	AUC T2D		AUC Cirrhosis
Method	w/o age+sex	w age+sex	w/o age+sex	w age+sex
RF	0.703	0.708	0.893	0.901
GBC	0.642	0.648	0.816	0.825
SVM	0.701	0.704	0.877	0.882
Lasso regression	0.665	0.670	0.823	0.831
Ridge regression	0.700	0.705	0.842	0.848
NB	0.682	0.685	0.802	0.807
CNN_basic	0.643	0.647	0.799	0.801
CNN_shuffle	0.712	0.718	0.844	0.852
taxoNN dis	0.720	0.725	0.903	0.908
taxoNN corr	0.733	0.762	0.911	0.938

Note: The results are reported on both studies considering model performance without (w/o) including age and sex and with (w) age and sex. Note that the last row (values in bold) shows the consistent improvement in the performance of the proposed model taxoNN_corr for both studies.