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Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction

by Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 17 - Number 8
Year of Publication: 2011
Authors: Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni
10.5120/2237-2860

Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni . Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction. International Journal of Computer Applications. 17, 8 ( March 2011), 43-48. DOI=10.5120/2237-2860

@article{ 10.5120/2237-2860,
author = { Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni },
title = { Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction },
journal = { International Journal of Computer Applications },
issue_date = { March 2011 },
volume = { 17 },
number = { 8 },
month = { March },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume17/number8/2237-2860/ },
doi = { 10.5120/2237-2860 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:05:06.163716+05:30
%A Jyoti Soni
%A Ujma Ansari
%A Dipesh Sharma
%A Sunita Soni
%T Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 17
%N 8
%P 43-48
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The healthcare environment is still ‘information rich’ but ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. This research paper intends to provide a survey of current techniques of knowledge discovery in databases using data mining techniques that are in use in today’s medical research particularly in Heart Disease Prediction. Number of experiment has been conducted to compare the performance of predictive data mining technique on the same dataset and the outcome reveals that Decision Tree outperforms and some time Bayesian classification is having similar accuracy as of decision tree but other predictive methods like KNN, Neural Networks, Classification based on clustering are not performing well. The second conclusion is that the accuracy of the Decision Tree and Bayesian Classification further improves after applying genetic algorithm to reduce the actual data size to get the optimal subset of attribute sufficient for heart disease prediction.

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Index Terms

Computer Science
Information Sciences

Keywords

KNN Neural Networks Bayesian classification Classification based on clustering Decision Tree