A Case Study of the Impact of Parental Diseases on the Probability of Hypertension Using Data Mining Techniques

Abstract

Introduction: Hypertension is one of the most common health problems. As it has a major impact on other serious diseases such as cardiovascular diseases and strokes, and due to not having any specific symptoms, it is known as a silent killer. Therefore, proper diagnosis, control, and treatment of hypertension is crucial in health care systems and will indeed prevent the development of the other diseases affected by. Studies have shown a strong connection between some diseases of parents and the probability of having hypertension in children. Method: In this study, using data collected from two health centers in Ardabil province and applying data mining techniques and Rapid Miner software, the impact of parental diseases on the probability of hypertension in children was investigated. Results: The results indicated that using paternal medical history on hypertension, premature coronary artery disease, hypercholesterolemia, and hyperthyroidism has a significant role in predicting hypertension in children. Moreover, the performance of the predictive model, developed using the collected samples and data mining techniques, was enhanced by 5%. Conclusion: Some diseases of parents, especially hypertension, increase the risk of hypertension in children. However, individual characteristics are the major determinants of this complication.

Keywords

• hypertension
• artificial intelligence
• machine learning
• data mining
• prediction
• paternal medical history