• Corpus ID: 114472903

Review on Heart Disease Prediction System using Data Mining Techniques

@inproceedings{Kaur2014ReviewOH,
  title={Review on Heart Disease Prediction System using Data Mining Techniques},
  author={Beant Kaur and Williamjeet Singh},
  year={2014}
}
Data mining is the computer based process of analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict future trends, allowing business to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally taken much time consuming to resolve. The huge amounts of data generated for prediction of heart disease are too complex and voluminous to be processed and analyzed by traditional methods. Data mining… 

Figures and Tables from this paper

Heart Disease Prediction System Using Data Mining Techniques - A Review
TLDR
This paper surveyes different papers in which one or more algorithms of data mining are used for the prediction of heart disease and shows that a SVM provide effective and efficient accuracy as compared to other data mining techniques in the predictionof heart disease.
A Review-Heart Disease Forecasting Pattern using Various Data Mining Techniques
TLDR
The overall review of heart disease prediction using various data mining techniques is discussed, which take less time and make process fast for the prediction system to predict heart disease with good accuracy in order to improve health.
Heart Disease Prediction using Genetic Algorithm with Rule Based Classifier in Data Mining
TLDR
A genetic algorithm is proposed for the prediction of heart disease using rule based classifier which provide results in the form of Decision Table which provide reliable performance in diagnosing heart disease.
Heart Disease Prediction System using Data Mining Techniques: A study
TLDR
The important role played by data mining tools in analyzing huge volumes of healthcare related data in prediction and diagnosis of disease is highlighted.
Identification and Predicting Heart Disease with Data Mining methods-A Survey
TLDR
A new fuzzy neural genetic approach is proposed which can exhibit much better performance for earlier heart disease prediction when compared to existing methods.
A survey on data mining techniques used in medicine
TLDR
An overview of data mining applications in medicine is presented to provide a clear view of the challenges and previous works in this area for researchers and to analyze and compare different data mining techniques used in the medical applications.
Prediction of Heart Disease using Supervised Learning Algorithms
TLDR
This paper aims at analyzing the various data mining techniques namely Decision Trees, Naive Bayes, Neural Networks, Random Forest Classification and Support Vector Machine by using the Cleveland dataset for Heart disease prediction to provide a quick and easy understanding of various prediction models in data mining.
Comparative Study-Prediction of Diabetes and Heart Disease using Data Mining Approaches
TLDR
This study and comparison is done of different data mining techniques used for prediction of diabetes and heart disease from clinical dataset with different accuracy.
A survey on Intelligent Data Mining Techniques used in Heart Disease Prediction
  • A. Rane
  • Computer Science
    2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS)
  • 2018
TLDR
It is revealed from this survey, even though usage of one data mining technique performs well, hybrid data mining techniques yield promising outcomes in the determination of coronary illness.
Survey on Prediction of Kidney Disease by using Data Mining Techniques
TLDR
The main objective of this paper is to analyze the application of data mining in the medical field and some of the techniques used in predicting kidney disease.
...
...

References

SHOWING 1-10 OF 48 REFERENCES
Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques
TLDR
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.
PERFORMANCE ANALYSIS OF CLASSIFICATION DATA MINING TECHNIQUES OVER HEART DISEASE DATA BASE
TLDR
This paper describes about a prototype using data mining techniques, namely Naïve Bayes and WAC (weighted associative classifier), which can answer complex “what if” queries which traditional decision support systems cannot.
Intelligent heart disease prediction system using data mining techniques
  • S. Palaniappan, R. Awang
  • Computer Science
    2008 IEEE/ACS International Conference on Computer Systems and Applications
  • 2008
TLDR
This research has developed a prototype Intelligent Heart Disease Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naive Bayes and Neural Network, which shows that each technique has its unique strength in realizing the objectives of the defined mining goals.
A Data Mining Approach for Prediction of Heart Disease Using Neural Networks
TLDR
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.
Heart disease Prediction System Using data Mining Techniques
  • S. Jain
  • Medicine, Computer Science
  • 2013
TLDR
The purpose of this paper is to develop a cost effective treatment using data mining technologies for facilitating data base decision support system for cardiovascular disease.
A Review on Data mining from Past to the Future
TLDR
The various improvements in the field of data mining from past to the present is discussed and the future trends are explored.
An Analysis of Heart Disease Prediction using Different Data Mining Techniques
TLDR
The observations reveal that Neural networks with 15 attributes has outperformed over all other data mining techniques for heart disease prediction and decision tree has also shown good accuracy with the help of genetic algorithm and feature subset selection.
Extraction of Significant Patterns from Heart Disease Warehouses for Heart Attack Prediction
TLDR
This paper has proposed an efficient approach for the extraction of significant patterns from the heart disease warehouses for heart attack prediction using the MAFIA algorithm.
Extraction of Significant Patterns from Heart Disease Warehouses for Heart Attack Prediction
TLDR
This paper has proposed an efficient approach for the extraction of significant patterns from the heart disease warehouses for heart attack prediction using the MAFIA algorithm.
A Prototype of Cancer/Heart Disease Prediction Model Using Data Mining
TLDR
A prototype model for the breast cancer as well as heart disease prediction using data mining techniques is presented and two decision tree algorithms C4.5 and the C5.0 are compared.
...
...