ICTACT Journal on Soft Computing

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Computational Approaches for Heart Disease Prediction-A Review


Affiliations
1 Department of Computer Science, Arignar Anna Government Arts College, India
     

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The data mining techniques can be primarily used to extract the potentially useful hidden knowledge from the large volume of health care industry databases for predicting the diseases. It is also assist to locate the relationships and patterns among the extracted data. In this paper, detailed survey of various computational techniques used in health care industry for predicting the heart diseases is presented. The issues facing by the computational models are identified while predicting the heart diseases and the same is also presented with future possible research directions.

Keywords

Data Mining, Heart Disease, Classification, Prediction, Parameters.
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  • Chaitrali S. Dangare and Sulabha S. Apte, “A Data Mining Approach for Prediction of Heart Disease using Neural Networks”, International Journal of Computer Engineering and Technology, Vol. 3, No. 3, pp. 23-29, 2012.

  • Resul Das, Ibrahim Turkoglu and Abdulkadir Sengur, “Diagnosis of Valvular Heart Disease through Neural Networks Ensembles”, Elsevier, 2009.

  • M. Anbarasi, E. Anupriya and N. Iyengar, “Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm”, International Journal of Engineering Science and Technology, Vol. 2, No. 10, pp. 5370-5376, 2010.

  • A. Rajkumar and G.S. Reena, “Diagnosis of Heart Disease using Data Mining Algorithm”, Global Journal of Computer Science and Technology, Vol. 10, No. 10, pp. 788-797, 2010.

  • Milan Kumari and S. Godara, “Comparative Study of Data Mining Classification Methods in Cardiovascular Disease Prediction”, International Journal of Computer Science and Technology, Vol. 2, No. 2, pp. 304-308, 2011.

  • N. Aditya Sundar, P. Pushpa Latha, M. Rama Chandra, “Performance Analysis of Classification Data Mining Techniques over Heart Disease Data Base”, International Journal of Engineering Science and Advanced Technology, Vol. 2, No. 3, pp. 470-478, 2013.

  • T. John Peter and K. Somasundaram, “Study and Development of Novel Feature Selection Framework for Heart Disease Prediction”, International Journal of Scientific and Research Publications, Vol. 2, No. 10, pp. 1-7, 2012.

  • Mai Shouman, Tim Turner and Rob Stocker “Applying K-Nearest Neighbour in Diagnosing Heart Disease Patients”, Proceedings of International Conference on Knowledge Discovery, pp. 23-29, 2012.

  • Nidhi Bhatla and Kiran Jyoti, “An Analysis of Heart Disease Prediction using Different Data Mining Techniques”, International Journal of Engineering Research and Technology, Vol. 1, No. 8, pp. 1-4, 2012.

  • A. Pethalakshmi and A. Anushya, “Effective Features Selection via Futuristic Genetic on Heart Data”, International Journal of Computational Intelligence and Informatics, Vol. 2, No. 1, pp. 23-27, 2012.

  • Abhishek Taneja, “Heart Disease Prediction System using Data Mining Techniques”, Oriental Scientific Publishing, 2013.

  • R. Chitra and V. Seenivasagam, “Heart Disease Prediction System using Supervised Learning Classifier”, Bonfring International Journal of Software Engineering and Soft Computing, Vol. 3, No. 1, pp. 1-7, 2013.

  • S. Indira and Fal Dessai, “Intelligent Heart Disease Prediction System using Probabilistic Neural Network”, International Journal on Advanced Computer Theory and Engineering, Vol. 4, No. 2, pp. 33-43, 2013.

  • Shamsher Bahadur Patel, Pramod Kumar Yadav and D.P. Shukla, “Predict the Diagnosis of Heart Disease Patients using Classification Mining Techniques”, IOSR Journal of Agriculture and Veterinary Science, Vol. 4, No. 2, pp. 61-64, 2014.

  • Vikas Chaurasia and Saurabh Pal, “Early Prediction of Heart Diseases using Data Mining Techniques”, Caribbean Journal of Science and Technology, Vol. 1, pp. 208-217, 2013.

  • Aditya Methaila, Prince Kansal, Himanshu Arya and Pankaj Kumar, “Early Heart Disease Prediction using Data Mining Techniques”, Proceedings of International Conference on Bioscience and Bioinformatics, pp. 53-59, 2014.

  • Kittipal Wisaeng, “Predict the Diagnosis of Heart Disease using Feature Selection and K-Nearest Neighbor Algorithm”, Applied Mathematical Sciences, Vol. 8, No. 83, pp. 4103-4113, 2014.

  • Nilakshi P. Waghulde and Nilima P. Patil, “Genetic Neural Approach for Heart Disease Prediction”, International Journal of Advanced Computer Research, Vol. 4, No. 3, pp. 331-338, 2014.

  • R. Chitra and V. Seenivasagam, “Review of Heart Disease Prediction System using Data Mining and Hybrid Intelligent Techniques”, ICTACT Journal on Soft Computing, Vol. 3, No. 4, pp. 605-609, 2013.

  • Rupali R. Patil, “Heart Disease Prediction System using Naive Bayes and Jelinek-Mercer Smoothing”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, No. 5, pp. 515-523, 2014.

  • B. Venkatalakshmi and M.V. Shivsankar, “Heart Disease Diagnosis using Predictive Data mining”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 3, No. 3, pp. 223-229, 2014.

  • A. Jarad, R. Katkar, A. Rehaman Shaikh and A. Salve, “Intelligent Heart Disease Prediction System with MONGODB”, International Journal of Emerging Trends and Technology in Computer Science, Vol. 4, No. 1, pp. 410-417, 2015.

  • Andrea D. Souza, “Heart Disease Prediction using Data Mining Techniques”, International Journal of Research in Engineering and Science, Vol. 3, No. 3, pp. 74-77, 2015.

  • B.V. Baiju and R.J. Remy Janet, “A Survey on Heart Disease Diagnosis and Prediction using Naive Bayes in Data Mining”, International Journal of Computer Engineering and Technology, Vol. 5, No. 2, pp. 1034-1038, 2015.

  • Moloud Adbar et al., “Comparing Performance of Data Mining algorithms in Prediction Heart Diseases”, International Journal of Electrical and Computer Engineering, Vol. 5, No. 6, pp. 1569-1576, 2015.

  • Rajwant Kaur and Sukhpreet Kaur, “Prediction of Heart disease Based on Risk Factors Using Genetic SVM Classifier”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 12, pp. 205-208, 2015.

  • B. Shinde Swati, “Decision Support System on Prediction of Heart Disease using Data Mining Techniques”, International Journal of Engineering Research and General Science, Vol. 3, No. 2, pp. 1453-1461, 2015.

  • Jaymin Patel, Teja Upadhyay and Samir Patel, “Heart Disease Prediction using Machine Learning and Data Mining Techniques”, International Journal of Computer Science and Communication, Vol. 7, No. 1, pp. 129-137, 2016.

  • K. Rajalakshmi and K. Nirmala, “Heart Disease Prediction with Map Reduce by using Weighted Association Classifier

  • and K-Means”, Indian Journal of Science and Technology, Vol. 9, No. 19, pp. 231-237, 2016.

  • S. Suganya and P. Tamil Selvi, “A Proficient Heart Disease Prediction Method using Fuzzy-Cart Algorithm”, International Journal of Scientific Engineering and Applied Science, Vol. 2, No. 1, pp. 1-6, 2016.

  • T. Karthikeyan and V.A. Kanimozhi, “Deep Learning Approach for Prediction of Heart Disease using Data mining Classification Algorithm Deep Belief Network”, International Journal of Advanced Research in Science, Engineering and Technology, Vol. 4, No. 1, pp. 3194-3201, 2017.

  • Rishabh Wadhawan, “Prediction of Coronary Heart Disease using Apriori algorithm with Data Mining Classification”, International Journal of Research in Science and Technology, Vol. 3, No. 1, pp. 1-15, 2018.

  • K. Srinivas, B.K. Rani and A. Govrdhan, “Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks”, International Journal on Computer Science and Engineering, Vol. 2, No. 2, pp. 250-255, 2010.

  • Rashedur M. Rahman and Farhana Afroz, “Comparison of Various Classification Techniques Using Different Data Mining Tools for Diabetes Diagnosis”, Journal of Software Engineering and Applications, Vol. 6, No. 3, pp. 85-97, 2013.


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  • Computational Approaches for Heart Disease Prediction-A Review

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Authors

R. Manavalan
Department of Computer Science, Arignar Anna Government Arts College, India
S. Saranya
Department of Computer Science, Arignar Anna Government Arts College, India

Abstract


The data mining techniques can be primarily used to extract the potentially useful hidden knowledge from the large volume of health care industry databases for predicting the diseases. It is also assist to locate the relationships and patterns among the extracted data. In this paper, detailed survey of various computational techniques used in health care industry for predicting the heart diseases is presented. The issues facing by the computational models are identified while predicting the heart diseases and the same is also presented with future possible research directions.

Keywords


Data Mining, Heart Disease, Classification, Prediction, Parameters.

References