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Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques

M. Dey1 , S.S. Rautaray2

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-4 , Page no. 82-98, Apr-2014

Online published on Apr 30, 2014

Copyright © M. Dey, S.S. Rautaray . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M. Dey, S.S. Rautaray, “Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.82-98, 2014.

MLA Style Citation: M. Dey, S.S. Rautaray "Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques." International Journal of Computer Sciences and Engineering 2.4 (2014): 82-98.

APA Style Citation: M. Dey, S.S. Rautaray, (2014). Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques. International Journal of Computer Sciences and Engineering, 2(4), 82-98.

BibTex Style Citation:
@article{Dey_2014,
author = {M. Dey, S.S. Rautaray},
title = {Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2014},
volume = {2},
Issue = {4},
month = {4},
year = {2014},
issn = {2347-2693},
pages = {82-98},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=115},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=115
TI - Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - M. Dey, S.S. Rautaray
PY - 2014
DA - 2014/04/30
PB - IJCSE, Indore, INDIA
SP - 82-98
IS - 4
VL - 2
SN - 2347-2693
ER -

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Abstract

Data mining technology provides a user oriented approach to extract the hidden information from the large database. There are different algorithms used in data mining techniques like decision tree, Bayesian classifier, naive Bayes, neural network, , clustering etc. . Data mining in healthcare medicine deals with learning models to predict patients� disease. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The main goal of this paper is to analyze and implement the data mining algorithms using WEKA tool and comparison between c4.5 and Bayesian classifier.

Key-Words / Index Term

Bayesian Classification, Bayesian Networks, C4.5, Neural Network

References

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