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An Efficient Algorithm for Disease Prediction with Multi Dimensional Data

by Smitha. T, V. Sundaram
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 9
Year of Publication: 2013
Authors: Smitha. T, V. Sundaram
10.5120/10491-5247

Smitha. T, V. Sundaram . An Efficient Algorithm for Disease Prediction with Multi Dimensional Data. International Journal of Computer Applications. 63, 9 ( February 2013), 1-4. DOI=10.5120/10491-5247

@article{ 10.5120/10491-5247,
author = { Smitha. T, V. Sundaram },
title = { An Efficient Algorithm for Disease Prediction with Multi Dimensional Data },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 9 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number9/10491-5247/ },
doi = { 10.5120/10491-5247 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:13:50.915567+05:30
%A Smitha. T
%A V. Sundaram
%T An Efficient Algorithm for Disease Prediction with Multi Dimensional Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 9
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main objective of this study is to create a fast, easy and an efficient algorithm for disease prediction , with less error rate and can apply with even large data sets and show reasonable patterns with dependent variables. For disease identification and prediction in data mining a new hybrid algorithm was constructed. The Disease Identification and Prediction(DIP) algorithm, which is the combination of decision tree and association rule is used to predict the chances of some of the disease hits in some particular areas. It also shows the relationship between different parameters for the prediction. To implement this algorithm using vb. net software was also developed.

References
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Index Terms

Computer Science
Information Sciences

Keywords

association rule clustering decision tree multidimensional data

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