Comparative Analysis for Heart Disease Prediction

JOIV: International Journal on Informatics Visualization

Jamaluddin Mir¹  Asim Shahzad¹  Arif Ullah¹  Muhammad Aamir¹  Nazri Mohd Nawi¹  Muhammad Faheem Mushtaq¹  Sundas Naqeeb Khan¹ 

[1] Universiti Tun Hussein Onn Malaysia, Johor, Malaysia;

关键词: classifiers;    heart disease analysis;   

DOI  :  10.30630/joiv.1.4-2.66

来源: DOAJ

【 摘 要 】

Today, heart diseases have become one of the leading causes of deaths in nationwide. The best prevention for this disease is to have an early system that can predict the early symptoms which can save more life. Recently research in data mining had gained a lot of attention and had been used in different kind of applications including in medical. The use of data mining techniques can help researchers in predicting the probability of getting heart diseases among susceptible patients. Among prior studies, several researchers articulated their efforts for finding a best possible technique for heart disease prediction model. This study aims to draw a comparison among different algorithms used to predict heart diseases. The results of this paper will helps towards developing an understanding of the recent methodologies used for heart disease prediction models. This paper presents analysis results of significant data mining techniques that can be used in developing highly accurate and efficient prediction model which will help doctors in reducing the number of deaths cause by heart disease.

【 授权许可】

Unknown