A Risk Factors Screening Method in the Context-aware System of Hypertension

Hypertension has become a health problem that seriously endangers human life and is the leading cause of cardiovascular disease. Many patients do not know exactly whether their blood pressure is well controlled or not, which makes their conditions worse. A context-aware intelligent system can help patients to analyse their control situation of blood pressure (BP) and provide feedback. It is especially important to determine whether the risk-factors input in the context-aware system of hypertension is appropriate. The choice of risk factors will affect the classification performance and accuracy of the system. The risk factors screening method for hypertension proposed in this paper combined the random forest algorithm and stability selection (RFSS). It can remove the redundant context information, and leave the key factors of BP control situation. Experimental results showed that the prediction accuracy achieved more than 77% prediction accuracy, and dimension of risk factors reduced by 59%. The results indicated that RFSS is an effective method in the screening of risk factors and the prediction of hypertension.