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International Journal of Scientific Development and Research - IJSDR
(An International Open Access Journal)
ISSN:
2455-2631


Issue: November 2021

Volume 6 | Issue 11

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Published Paper Details
Paper Title: Heart Disease Prediction Using Machine Learning
Authors Name: Karpagam.S , Kaleeswari.M , Kavitha.K , Dr.S.Priyadarsini
Unique Id: IJSDR2008043
Published In: Volume 5 Issue 8, August-2020
Abstract: Heart Attack is a term that assigns a large number of medical conditions related to heart. The key to Heart (Cardiovascular) diseases to evaluate large scores of data sets, compare information that can be used to predict, Prevent, Manage such as Heart attacks. The main objective of this research is to develop an Intelligent System using machine learning technique, namely, Naive Bayes, KNN, Random forest Decision tree. It is implemented as web based application in this user answers the predefined questions. Data analytics is used to incorporate world for its valuable use to controlling, contravasting and Manage a large data sets. It can be applied with an much success to predict, prevent, Managing a Cardiovascular Diseases. To solve this we aims to implement the Data Analytics based on SVM and Genetic Algorithm to diagnosis of heart diseases. This result reveal which Algorithm is best optimized Prediction Models. It can answer complex queries for diagnosing heart disease and thus assist healthcare practitioners to make intelligent clinical decisions which traditional decision support systems cannot. By providing effective treatments, it also helps to reduce treatment costs
Keywords: SVM, KNN, Cardiovascular disease etc…
Cite Article: "Heart Disease Prediction Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 8, page no.334 - 337, August-2020, Available :http://www.ijsdr.org/papers/IJSDR2008043.pdf
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Publication Details: Published Paper ID: IJSDR2008043
Registration ID:192339
Published In: Volume 5 Issue 8, August-2020
DOI (Digital Object Identifier):
Page No: 334 - 337
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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