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Prediction of Heart Disease Using Data Mining Technique

Ranjana Joshi1 , Shilpa Sethi2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 305-309, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.305309

Online published on Dec 31, 2018

Copyright © Ranjana Joshi, Shilpa Sethi . 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: Ranjana Joshi, Shilpa Sethi, “Prediction of Heart Disease Using Data Mining Technique,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.305-309, 2018.

MLA Style Citation: Ranjana Joshi, Shilpa Sethi "Prediction of Heart Disease Using Data Mining Technique." International Journal of Computer Sciences and Engineering 6.12 (2018): 305-309.

APA Style Citation: Ranjana Joshi, Shilpa Sethi, (2018). Prediction of Heart Disease Using Data Mining Technique. International Journal of Computer Sciences and Engineering, 6(12), 305-309.

BibTex Style Citation:
@article{Joshi_2018,
author = {Ranjana Joshi, Shilpa Sethi},
title = {Prediction of Heart Disease Using Data Mining Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {12},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {305-309},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3333},
doi = {https://doi.org/10.26438/ijcse/v6i12.305309}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i12.305309}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3333
TI - Prediction of Heart Disease Using Data Mining Technique
T2 - International Journal of Computer Sciences and Engineering
AU - Ranjana Joshi, Shilpa Sethi
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 305-309
IS - 12
VL - 6
SN - 2347-2693
ER -

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Abstract

In the past few decades, heart diseases had been found as leading cause of death across the world. But at the same time, it is also discovered as most preventable and controllable disease. Further, it is identified that its early and timely diagnosis helps in controlling its growth and reducing treatment cost remarkably. So it become essential to discover accurate and reasonable tools capable of extracting high risk data for timely diagnosis of such a critical disease The proposed work aims to identify vital parameters leading to heart diseases and develop a model based on data mining techniques.

Key-Words / Index Term

Data mining, Heart disease Prediction, Naive Bayes, Technique

References

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