Heart Disease Prediction System
Author(s):
Saloni Choudhary, Pratik Dave, Aryaman Jha, Jenil Kumbhani
Keywords:
Machine Learning Algorithms, EHR, Particle Swarm Optimization, Forward Selection, Backward Elimination.
Abstract
A prevalent cardiovascular condition that can alter an individual's life, heart disease is very expensive for both individuals and healthcare systems. Effective prevention strategies and early diagnosis are necessary as it progresses to be a major global societal well-being concern. Improving patient outcomes and cutting costs associated with healthcare requires early detection and proactive management. Based on a variety of patient characteristics and medical data, machine-learning characteristics, classifiers, and algorithms have demonstrated promise in the past several years in the prediction of cardiac disease risk. This abstract describes the application of machine learning methods to the construction of a prediction system for cardiac disease. This abstract analyzes patient data, such as electronic health records (EHR), medical histories, vital signs, and diagnostic test results, using sophisticated algorithms. The principal aim of the system is to precisely detect individuals who are susceptible to heart failure through the application of particle swarm optimization, forward selection, and backward elimination techniques. This will facilitate early intervention and tailored care, with 0 signifying the non-existence of heart disease and 1 signifying its presence.
Article Details
Unique Paper ID: 166953

Publication Volume & Issue: Volume 11, Issue 3

Page(s): 37 - 40
Article Preview & Download


Share This Article

Join our RMS



Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Latest Publication

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers