Proceedings ArticleDOI
Human heart disease prediction system using data mining techniques
J. Thomas,R Theresa Princy +1 more
- pp 1-5
TLDR
This paper gives the survey about different classification techniques used for predicting the risk level of each person based on age, gender, Blood pressure, cholesterol, pulse rate using Naïve Bayes, KNN, Decision Tree Algorithm, Neural Network.Abstract:
Nowadays, health disease are increasing day by day due to life style, hereditary. Especially, heart disease has become more common these days, i.e. life of people is at risk. Each individual has different values for Blood pressure, cholesterol and pulse rate. But according to medically proven results the normal values of Blood pressure is 120/90, cholesterol is and pulse rate is 72. This paper gives the survey about different classification techniques used for predicting the risk level of each person based on age, gender, Blood pressure, cholesterol, pulse rate. The patient risk level is classified using datamining classification techniques such as Naive Bayes, KNN, Decision Tree Algorithm, Neural Network. etc., Accuracy of the risk level is high when using more number of attributes.read more
Citations
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Journal ArticleDOI
Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques
TL;DR: This paper proposes a novel method that aims at finding significant features by applying machine learning techniques resulting in improving the accuracy in the prediction of cardiovascular disease with the hybrid random forest with a linear model (HRFLM).
Proceedings ArticleDOI
Design And Implementing Heart Disease Prediction Using Naives Bayesian
TL;DR: The research elaborates and presents multiple knowledge abstraction techniques by making use of data mining methods which are adopted for heart disease prediction, and reveals that the established diagnostic system effectively assists in predicting risk factors concerning heart diseases.
Journal ArticleDOI
Feature Analysis of Coronary Artery Heart Disease Data Sets
TL;DR: This work applies an integration of the results of the machine learning analysis applied on different data sets targeting the CAD disease to avoid the missing, incorrect, and inconsistent data problems that may appear in the data collection.
Book ChapterDOI
Decision Tree Algorithms for Prediction of Heart Disease
Srabanti Maji,Srishti Arora +1 more
TL;DR: In this paper, a hybridization technique is proposed in which decision tree and artificial neural network classifiers are hybridized for better performance of prediction of heart disease, which is done using WEKA.
Book ChapterDOI
Hybrid Approach for Heart Disease Prediction Using Data Mining Techniques
M. Tarawneh,Ossama Embarak +1 more
TL;DR: New heart disease prediction system that combine all techniques into one single algorithm, it called hybridization is proposed, and the result confirm that accurate diagnose can be taken by using a combined model from all techniques.
References
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Journal ArticleDOI
Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques
TL;DR: This paper has analysed prediction systems for Heart disease using more number of input attributes and shows that out of these three classification models Neural Networks predicts Heart disease with highest accuracy.
Journal ArticleDOI
Association rule discovery with the train and test approach for heart disease prediction
TL;DR: An algorithm is introduced that uses search constraints to reduce the number of rules, searches for association rules on a training set, and finally validates them on an independent test set to produce a set of rules with high predictive accuracy.
Proceedings ArticleDOI
Genetic neural network based data mining in prediction of heart disease using risk factors
TL;DR: A technique for prediction of heart disease using major risk factors involves two most successful data mining tools, neural networks and genetic algorithms and was implemented in Matlab and predicts the risk of heart diseases with an accuracy of 89%.
Posted Content
A data mining approach for prediction of heart disease using neural networks
S. Dangare,Sulabha S. Apte +1 more
TL;DR: A Heart Disease Prediction system (HDPS) is developed using Neural network, which predicts the likelihood of patient getting a Heart disease with nearly 100% accuracy.
Journal ArticleDOI
Review of heart disease prediction system using data mining and hybrid intelligent techniques
R. Chitra,V. Seenivasagam +1 more
TL;DR: In this article, the authors summarized the commonly used techniques for heart disease prediction and their complexities are summarized in this paper and observed that Hybrid Intelligent Algorithm improves the accuracy of the prediction system.