Heart Disease Prediction Using ML Algorithm

Author:

Deshmukh Atharva1ORCID,Tyagi Amit Kumar2ORCID,Toppo Sangita Krishnaram1

Affiliation:

1. Terna Engineering College, India

2. Vellore Institute of Technology, India

Abstract

Many patients don't get proper treatment due to a shortage of doctors. Thus, predicting a disease using the patient's symptoms has become an important task these days. To solve this there must be a predicting system for predicting diseases. In this chapter, a model is proposed for predicting the disease suffered by a person by knowing the symptoms. The model uses the logistic regression algorithm, which assigns observations to a discrete set of classes and provides a good level of accuracy. It collects the data of a person's symptoms and suggests a suitable disease accordingly. To showcase the accuracy of the proposed model, it has been implemented on a heart disease dataset to predict the occurrence of heart disease. The implementation will illustrate the effectiveness of the proposed model, which can help in the development of an intelligent healthcare system and reduce the cost of treatment.

Publisher

IGI Global

Reference30 articles.

1. A data mining model to predict and analyze the events related to coronary heart disease using decision trees with particle swarm optimization for feature selection.;A. S.Abdullah;International Journal of Computers and Applications,2012

2. Deep learning approach for active classification of electrocardiogram signals.;M. M.Al Rahhal;Information Sciences,2016

3. Heart disease diagnosis using data mining technique

4. Disease forecasting system using data mining methods.;M. N.Banu;2014 International conference on intelligent computing applications,2014

5. Survey on prediction and analysis the occurrence of heart disease using data mining techniques.;C.Beyene;International Journal of Pure and Applied Mathematics,2018

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