ABSTRACT

Hypertension, defined by elevated blood pressure throughout the body, is currently the leading risk factor for cardiovascular and cerebrovascular diseases, and the primary cause of death associated with these conditions. The lack of a large number of studies using data mining technology to analyze hypertension is mainly due to the medical community’s incomplete understanding of the etiology of hypertension and the lack of comprehensive understanding of its influencing factors. In this study, data mining technology was used to analyze more than 5000 data of hypertension patients in community hospitals to explore the key factors affecting hypertension. Through the decision tree algorithm modeling, a high accuracy prediction model is constructed, and a management system is developed to realize the decision support of early warning and prevention of hypertension, which is in line with the ISO 25010 standard.

Keywords: hypertension, data mining, decision tree, prediction, potential hypertension, system evaluation, modeling
https://doi.org/ 10.57180/gdir7033