Table 2.

Predictive performance on hypertension dataset

Dataset	Model	KNN	RF	SVR	Ridge	Lasso	MTLasso	MLP-4	GATAN-1	GATAN-2
Full feature set	MSE	248.06	214.68	299.03	261.52	205.67	217.34	209.43	199.76	203.50
		(60.73)	(25.18)	(82.16)	(23.26)	(36.07)	(39.35)	(28.36)	(33.48)	(29.98)
	EVS	0.26	0.29	0.08	0.10	0.33	0.30	0.32	0.36	0.34
		(0.18)	(0.12)	(0.02)	(0.37)	(0.11)	(0.14)	(0.14)	(0.10)	(0.14)
	MAE	10.91	11.29	11.66	12.41	11.40	11.65	10.43	10.20	10.77
		(2.05)	(1.97)	(1.93)	(1.65)	(2.58)	(2.53)	(2.02)	(1.71)	(2.10)
Lab and demo	MSE	282.06	261.27	284.05	278.80	250.754	253.59	243.41	237.97	237.66
		(39.58)	(20.56)	(58.15)	(18.88)	(26.01)	(33.79)	(31.87)	(33.59)	(34.09)
	EVS	0.06	0.08	0.06	0.03	0.15	0.14	0.17	0.19	0.19
		(0.17)	(0.25)	(0.01)	(0.22)	(0.11)	(0.11)	(0.10)	(0.09)	(0.10)
	MAE	10.54	10.42	9.90	10.24	9.59	9.43	8.84	8.67	8.54
		(2.38)	(0.95)	(1.24)	(1.78)	(1.26)	(0.94)	(1.96)	(2.05)	(2.01)

The first section uses a full set of features; the second only uses lab results and demographic information

The best performance is bolded