Fig. 4From: Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learningPersonalized survival prediction by using (a) LMTLR model, (b) NMTLR model, (c) RSF model and (d) CoxPH model when randomly identifying two patients as an example. X axis is survival time in years, Y axis is survival probability. Patient one (red line) is a short survivor who lives for 4.0 years from diagnosis of hypertension to CVD, while patient two (blue line) is a long survivor whose survival time is censored at 4.9 years. Patient one developed CVD after 4.0 years diagnosed as hypertension, however, patient two was censored at 4.9 years after diagnosed as hypertension patient. The bottom position of survival time text (4.0 and 4.9) on the pictures correspond to 50% survival probability horizontal location line. Note: CoxPH = Cox’s proportional hazard, LMTL = linear multi-task logistic regression, NMTLR = neural multi-task logistic regression, RSF = random survival forestBack to article page