Algorithms Used For Optimizing K-Means For Heart Disease Diagnosis

Shimpli Borkar; Priyal Dharmawat; Sonali Dobhal; Shloka Harne

Algorithms Used For Optimizing K-Means For Heart Disease Diagnosis

Authors: Shimpli Borkar, Priyal Dharmawat, Sonali Dobhal, Shloka Harne

Unique Paper ID: 149187
Volume: 6
Issue: 11
PageNo: 200-204

Keywords: Heart disease Data Mining Clustering K-Means.

Abstract:
The heart is a significant organ of the human body. Life is reliant on the proper functioning of the heart. Most of the time is difficult to analyze a patient as a heart patient. For this purpose, data mining can be used to recognize a hidden clinical dataset. In this paper, we study to find ways to optimize the K-Means algorithm by overcoming its drawbacks which may help create a heart disease predicting system by applying it. Here, we present a study on the advanced data mining techniques and hybrid algorithms that could be used to optimize the K-Means and increase the prediction accuracy of the system of Heart disease prediction.

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Cite This Article

ISSN: 2349-6002
Volume: 6
Issue: 11
PageNo: 200-204

Algorithms Used For Optimizing K-Means For Heart Disease Diagnosis

Available:https://ijirt.org/Article?manuscript=149187

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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