Human Heart Disease Prediction System Using Data Mining Techniques

S. Javed, Hamza A. Javed, A. Saddique, Beenish Rafiq
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引用次数: 20

Abstract

— Prediction of heart disease is a big concern now a days because everyone is busy and due to heavy load of work people do not give attention to their health. To diagnose a disease is a big challenge. The issue is to extract data that have some meaningful knowledge. For this purpose, data mining techniques are used to extract meaningful data. Decision Tree and ID3 are used to predict heart diseases. Many researchers and practitioners are familiar with prediction of heart diseases and wide range of techniques is available to predict disease. To address this problem, Decision Tree is used to predict the heart disease. In this study the collected data is pre-processed, Decision Tree algorithm and ID3 were then applied to predict the heart disease.   Index Terms— Decision Tree, ID3 Algorithm, Data Mining, Decision Support System (DSS), knowledge Discovery from Databases (KDD).
基于数据挖掘技术的人类心脏病预测系统
-心脏病的预测是一个大问题,现在的日子,因为每个人都很忙,由于繁重的工作负荷,人们不注意自己的健康。诊断疾病是一个很大的挑战。问题是提取出具有一些有意义的知识的数据。为此,使用数据挖掘技术来提取有意义的数据。决策树和ID3用于预测心脏病。许多研究人员和从业人员都熟悉心脏病的预测,并且有广泛的技术可用于预测疾病。为了解决这个问题,决策树被用于预测心脏病。在本研究中,对收集到的数据进行预处理,然后应用决策树算法和ID3进行心脏病预测。索引术语-决策树,ID3算法,数据挖掘,决策支持系统(DSS),数据库知识发现(KDD)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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