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. 2020 Jul 6;8(7):e17257. doi: 10.2196/17257

Table 5.

Trends of model performance with increasing feature sets.

Variables included in the model Number of features AUCa ACCb
SBPc_last, Age, Gender, Years_After_Hypertension (in the last CHDd-free record) 4 0.7547 0.6941
+ Diabetes diagnosis 5 0.7766 0.7090
+ Hyperlipidemia diagnosis 6 0.8111 0.7339
+Inpatient diagnosis flag
+Total in-hospital days
+ Total in-hospital visit number
9 0.8134 0.7341
+ Diagnosed symptoms
(eg, hypertension level, cerebral disease, dizziness, nephropathy, gout, hyperuricemia, palpitation)
19 0.8289 0.7460
+ Multipoint SBP statistics
(SBP_max, SBP_min, SBP_mean)
22 0.8589 0.7766
+ Dynamic SBP trends
(SBP_ min(max.mean)_1st(2nd)_half)
28 0.8752 0.7929
+ Medical activities trends
(N_visits_1st_half, N_visits_2nd_half, Visit_trend_ratio)
31 0.9195 0.8350
+ Medical activities trends
(N_visits_last_3me, N_visits_last_6mf)
33 0.9427 0.8686

aAUC: area under the receiver operating characteristic curve.

bACC: accuracy.

cSBP: systolic blood pressure.

dCHD: coronary heart disease.

e3m: 3 months.

f6m: 6 months.