Abstract Proceedings of ICIRESM – 2019
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PREDICTION OF CARDIOLOGY DISORDER PREDICTION USING MACHINE LEARNING TECHNIQUES
Heart diseases are the most widely recognized reason for death worldwide. Initial identification of heart sickness and consistent supervision of specialists can diminish the mortality ratio. Now a day we use Machine Learning method to predict the cardiology disorder. This paper is proposed a comparative study to predict the Cardiology Disorder Prediction (CDP) and to select the best machine learning method. The aim is to predict heart disease accurately by using different supervised learning like Support Vector machine, Random Forest and Logistic regression on a comparison basis. The results shown that the Support Vector Machine (SVM) is the maximum classification accuracy, Logistic Regression is next better than the Random Forest.
Support Vector Machine, Machine Learning, Cardiology Disorder Prediction, Supervised Learning.
30/08/2019
148
19146
IMPORTANT DAYS
Paper Submission Last Date
February 27th, 2026
Notification of Acceptance
March 25th, 2026
Camera Ready Paper Submission & Author's Registration
April 20th, 2026
Date of Conference
May 29th, 2026