Heart Disease Classification: A Case Study using Machine Learning and Data Mining

Authors(4) :-Sourabh Kulkarni, Chaitra .D Bhat, Deepa Patil, Jovita Dara

The diagnostic of heart disease remains more or less the most difficult and tedious task in the medical field and it various factors and symptoms of prediction which is involved in several layered issue that could engender the negative presumptions and unpredictable effects. Wu et al proposed that the integration of clinical decision support with relation to the computer- based system of the patient record could reduce the rate of errors in medical predictions, low the unwanted practice variation, enhance safety for patients, and the improvement of patient outcome. This knowledge provides a useful environment which can help to significantly improve the quality of clinical decisions. Many of hospital information in recent days are designed to implement patient billing, patient data storing, inventory management and generation of simple statistics computation. Most of the hospitals use decision support systems but they are still in most cases bounded. The majority of doctors are predicting heart disease symptoms based on their learning and working experience. In this case, prediction system should be implemented so that to reduce the risk of Heart Disease.

Authors and Affiliations

Sourabh Kulkarni
Department of Computer Science and Engineering, K.L.E. Institute of Technology, Hubli, Karnataka, India
Chaitra .D Bhat
Department of Computer Science and Engineering, K.L.E. Institute of Technology, Hubli, Karnataka, India
Deepa Patil
Department of Computer Science and Engineering, K.L.E. Institute of Technology, Hubli, Karnataka, India
Jovita Dara
Department of Computer Science and Engineering, K.L.E. Institute of Technology, Hubli, Karnataka, India

Algorithms, Diseases, Heart-attack, Random forest, Decision trees , Data mining, Naive Bayes, Support Vector Machine.

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Publication Details

Published in : Volume 4 | Issue 6 | May-June 2018
Date of Publication : 2018-05-08
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 265-271
Manuscript Number : CSEIT184651
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sourabh Kulkarni, Chaitra .D Bhat, Deepa Patil, Jovita Dara, "Heart Disease Classification: A Case Study using Machine Learning and Data Mining", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 6, pp.265-271, May-June-2018.
Journal URL : http://ijsrcseit.com/CSEIT184651

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