Intelligent Heart Disease Prediction System Using Data Mining Techniques

被引：0
|
作者：
Palaniappan, Sellappan [1 ]
Awang, Rafiah [2 ]
机构：
[1] Dept Informat Technol, Block C,Kelana Sq,Jalan SS7/ 26, Kelana Jaya, Malaysia
[2] Malaysia Univ Sci & Technol, Selangor 47301, Malaysia
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2008年 / 8卷 / 08期
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not "mined" to discover hidden information for effective decision making. Discovery of hidden patterns and relationships often goes unexploited. Advanced data mining techniques can help remedy this situation. This research has developed a prototype Intelligent Heart Disease Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naive Bayes and Neural Network. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. IHDPS can answer complex "what if" queries which traditional decision support systems cannot. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It enables significant knowledge, e.g. patterns, relationships between medical factors related to heart disease, to be established. IHDPS is Web- based, user- friendly, scalable, reliable and expandable. It is implemented on the. NET platform.
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页码：343 / 350
页数：8
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