Establish A Predictive Model of Hypertension Complications

Exploring the relationship between hypertension and nutritional ingredients intake with machine learning

“…For the prediction of hypertension, Dong and Wang [15] studied the influencing factors of hypertension through improved back propagation neural network algorithms, including genetic factors, lifestyle factors, obesity, and a reasonable diet. Chai et al [16] established a predictive model for the complications of hypertension based on data mining technology. Zhang et al [17] proposed an improved C4.5 decision tree (DT) algorithm to predict hypertension using medical data from hospital patients, with a final accuracy of 81.58%.…”