USE ASSOCIATION RULES (A PRIORI ALGORITHM) TO STUDY THE RELATION BETWEEN VARIABLES THAT AFFECT HIGH BLOOD PRESSURE

Authors

  • Shahram Tahmasebian 1: School of Paramedical, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2: School of Management and Medical Information, Shiraz University of Medical Sciences, Shiraz, Iran. 3: School of Computer Engineering & IT, Shiraz University of Technology, Shiraz, Iran 4: Tehran University of Medical Sciences, Tehran, Iran

Keywords:

High blood pressure, Data mining, Association rules, A priori algorithm

Abstract

Abstract

Introduction: Due to the increasing development of industrial societies, special diseases have spread, particularly in Iran; thus, improper lifestyles of eating and physical activity has increased the prevalence of these diseases. One of these diseases is high blood pressure, which is the origin of many other diseases; thus, increase costs of the health budget are being allocated to treating high blood pressure. Usually the types of jobs, lack of exercise, and poor diet can have a large impact on the disease.

Methods: In this study, we try to use data mining algorithms to discover the important relation between disease and high blood pressure, which are effective features; thus, we obtained data on 1000 patients who entered our survey.

Results and Conclusion: This review was undertaken with association rules employment physical factors, and smoking in people with low blood pressure have been seen. Obesity BMI above the norm and low green fruit consumption in people with high blood pressure are associated.

 

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Published

2017-01-03

Issue

Vol. 2 No. 1 (2017): January- March 2017

Section

Articles