PREDICTION OF CARDIOVASCULAR DISEASES (CVDS) USING MACHINE LEARNING TECHNIQUES IN HEALTH CARE CENTERS

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Volume 4 (2), December 2021, Pages 267-279

Hafiz Gulfam Ahmad1, Muhammad Jasim Shah2

1 Ghazi University, Dera Ghazi Khan, Pakistan, This email address is being protected from spambots. You need JavaScript enabled to view it.

2 Emerson University Multan, Pakistan, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Cardiovascular Diseases (CVDs) are one of the most common health problems nowadays. Early diagnosis of heart disease is a significant concern for health professionals in medical centers. An incorrect forecast is more likely to have negative effects, such as disability or even death. Our research is motivated by the desire to predict cardiovascular diseases based on data mining that can be valuable to medical centers. Various data mining approaches are used for the early detection of cardiac diseases. This paper examines several research publications that work on various heart diseases. We compare and contrast several machine learning methods, such as KNN, ANN, Decision Tree, SVM, and Random Forest. We looked at 918 observations with several features related to heart disease. A comparative study with age and sex is established to predict cardiac disease using the decision tree approach. Our dataset contains 11 features that are used to forecast possible heart disease. One of the attributes indicates that the age factor has the most significant impact on heart disease. According to our findings, heart attacks cause four out of every five CVD deaths, with one-third of these deaths occurring suddenly in those under 70.

Keywords:

NN, ANN, Decision tree, SVM, Random forest.

DOI: https://doi.org/10.32010/26166127.2021.4.2.267.279

 

 

Reference 

Ajam, N. (2015). Heart diseases diagnoses using artificial neural network. IISTE Network and Complex Systems, 5(4).

Amin, M. S., Chiam, Y. K., & Varathan, K. D. (2019). Identification of significant features and data mining techniques in predicting heart disease. Telematics and Informatics, 36, 82-93. 

Anbarasi, M., Anupriya, E., & Iyengar, N. C. S. N. (2010). Enhanced prediction of heart disease with feature subset selection using genetic algorithm. International Journal of Engineering Science and Technology, 2(10), 5370-5376. 

Ansarullah, S.I., Sharma, P.K., Wahid, A. and Kirmani, M.M., 2016. Heart Disease Prediction System using Data Mining Techniques: A study. International Journal of Bio-Science and Bio-Technology 8(4), 139-148

Bahrami, B., & Shirvani, M. H. (2015). Prediction and diagnosis of heart disease by data mining techniques. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 2(2), 164-168.

Beyene, C., & Kamat, P. (2018). Survey on prediction and analysis the occurrence of heart disease using data mining techniques. International Journal of Pure and Applied Mathematics, 118(8), 165-174.

Bhatla, N. and Jyoti, K., 2012. An analysis of heart disease prediction using different data mining techniques. International Journal of Engineering, 1(8), pp.1-4.

Chadha, R., & Mayank, S. (2016). Prediction of heart disease using data mining techniques. CSI transactions on ICT, 4(2), 193-198. 

Dangare, C. and Apte, S., 2012. A data mining approach for prediction of heart disease using neural networks. International Journal of Computer Engineering and Technology (IJCET), 3(3).

Dangare, C. S., & Apte, S. S. (2012). Improved study of heart disease prediction system using data mining classification techniques. International Journal of Computer Applications, 47(10), 44-48.

Deepika, K., & Seema, S. (2016, July). Predictive analytics to prevent and control chronic diseases. In 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT) (pp. 381-386). IEEE.

Dwivedi, A. K. (2018). Performance evaluation of different machine learning techniques for prediction of heart disease. Neural Computing and Applications, 29(10), 685-693. 

Fedesoriano. (September 2021). Heart Failure Prediction Dataset. Retrieved from: https://www.kaggle.com/fedesoriano/heart-failure-prediction.

Fredrick David, H. B., & Belcy, S. A. (2018). Heart disease prediction using data mining techniques. ICTACT Journal on Soft Computing, 9(01), 1817-1823.

Jardan and Frinkn, J.K., 2012, May. Human heart disease prediction system using data mining    techniques. In 2012 international conference on circuit, power and computing technologies (ICCPCT) (pp. 1-5). IEEE.

Krishnaiah, V., Narsimha, G., & Chandra, N. S. (2016). Heart disease prediction system using data mining techniques and intelligent fuzzy approach: a review. International Journal of Computer Applications, 136(2), 43-51. 

Latha, C. B. C., & Jeeva, S. C. (2019). Improving the accuracy of prediction of heart disease risk based on ensemble classification techniques. Informatics in Medicine Unlocked, 16, 100203. 

Marimuthu, M., Abinaya, M., Hariesh, K. S., Madhankumar, K., & Pavithra, V. (2018). A review on heart disease prediction using machine learning and data analytics approach. International Journal of Computer Applications, 181(18), 20-25. 

Methaila, A., Kansal, P., Arya, H., & Kumar, P. (2014). Early heart disease prediction using data mining techniques. Computer Science & Information Technology Journal, 24, 53-59. 

Palaniappan, S. and Awang, R., 2008, March. Intelligent heart disease prediction system using data mining techniques. In 2008 IEEE/ACS international conference on computer systems and applications (pp. 108-115). IEEE.

Palaniappan, S., & Awang, R. (2008, March). Intelligent heart disease prediction system using data mining techniques. In 2008 IEEE/ACS international conference on computer systems and applications (pp. 108-115). IEEE. 

Prabhavathi, S., & Chitra, D. M. (2016). Analysis and prediction of various heart diseases using DNFS techniques. International Journal of Innovations in Scientific and Engineering Research, 2(1), 1-7. 

Rairikar, A., Kulkarni, V., Sabale, V., Kale, H. and Lamgunde, A., 2017, June. Heart disease prediction using data mining techniques. In 2017 International conference on intelligent computing and control (I2C2) (pp. 1-8). IEEE.

Rairikar, A., Kulkarni, V., Sabale, V., Kale, H., & Lamgunde, A. (2017, June). Heart disease prediction using data mining techniques. In 2017 International conference on intelligent computing and control (I2C2) (pp. 1-8). IEEE.

Raju, C., Philipsy, E., Chacko, S., Suresh, L. P., & Rajan, S. D. (2018, March). A survey on predicting heart disease using data mining techniques. In 2018 conference on emerging devices and smart systems (ICEDSS) (pp. 253-255). IEEE.

Reddy, M. P. S. C., Palagi, M. P., & Jaya, S. (2017). Heart disease prediction using ANN algorithm in data mining. International Journal of Computer Science and Mobile Computing, 6(4), 168-172.

Saleh, B., Saedi, A., Al-Aqbi, A., & Salman, L. (2020). Analysis of Weka Data Mining Techniques for Heart Disease Prediction System. International journal of medical reviews, 7(1), 15-24.

Saxena, K., & Sharma, R. (2016). Efficient heart disease prediction system. Procedia Computer Science, 85, 962-969.

Sharma, M., Singh, G. and Singh, R., 2017. Stark assessment of lifestyle based human disorders using data mining based learning techniques. IRBM, 38(6), pp.305-324.

Sharma, P., Saxena, K., & Sharma, R. (2016). Heart disease prediction system evaluation using C4. 5 rules and partial tree. In Computational intelligence in data mining—volume 2 (pp. 285-294). Springer, New Delhi.

Shetty, A., & Naik, C. (2016). Different data mining approaches for predicting heart disease. Int J Innov Res Sci Eng Technol, 5(9), 277-281.

Singh, P., Singh, S. and Pandi-Jain, G.S., 2018. Effective heart disease prediction system using data mining techniques. International journal of nanomedicine, 13(T-NANO 2014 Abstracts), p.121.

Srinivas, K., Rani, B.K. and Govrdhan, A., 2010. Applications of data mining techniques in healthcare and prediction of heart attacks. International Journal on Computer Science and Engineering (IJCSE), 2(02), pp.250-255.

Sultana, M., Haider, A. and Uddin, M.S., 2016, September. Analysis of data mining techniques for heart disease prediction. In 2016 3rd international conference on electrical engineering and information communication technology (ICEEICT) (pp. 1-5). IEEE.

Taneja, A. (2013). Heart disease prediction system using data mining techniques. Oriental Journal of Computer science and technology, 6(4), 457-466.

Thomas, J. and Princy, R.T., 2016, March. Human heart disease prediction system using data mining techniques. In 2016 international conference on circuit, power and computing technologies (ICCPCT) (pp. 1-5). IEEE.

Vijayashree, J., & SrimanNarayanaIyengar, N. C. (2016). Heart disease prediction system using data mining and hybrid intelligent techniques: A review. International Journal of Bio-Science and Bio-Technology, 8(4), 139-148. 

Yahaya, L., Oye, N. D., & Garba, E. J. (2020). A comprehensive review on heart disease prediction using data mining and machine learning techniques. American Journal of Artificial Intelligence, 4(1), 20-29.

Zriqat, I. A., Altamimi, A. M., & Azzeh, M. (2017). A comparative study for predicting heart diseases using data mining classification methods. arXiv preprint arXiv:1704.02799.