Heart Disease Prediction Using ML

International Journal of Computer Science and Engineering
© 2020 by SSRG - IJCSE Journal
Volume 7 Issue 6
Year of Publication : 2020
Authors : Vaibhav Gupta, Dr.Pallavi Murghai Goel

How to Cite?

Vaibhav Gupta, Dr.Pallavi Murghai Goel, "Heart Disease Prediction Using ML," SSRG International Journal of Computer Science and Engineering , vol. 7,  no. 6, pp. 17-19, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I6P105


Cardiac disease is a major cause of death throughout the world. It is hard to know or predict by medical practitioners as it requires expertise and higher knowledge of prediction. The environment in healthcare sector is information rich but it have lacks of knowledge. A lot of data is available in healthcare systems over the internet but there is a lack of effective analysis tool to discover hidden patterns in data. An automated or self-made system will increase medical efficiency and decrease cost and time. This software goal to know or predict the occurrence of a disease based on the data which is collected from Kaggle. The Main aim is to extract the hidden patterns by applying Machine Learning techniques on the dataset and to predict or know the presence value on a scale. The prediction of heart disease requires a large size of data which is too massive and complex to process and Analysis by conventional technique. Our goal is to find out an suitable technique that is efficient and accurate for prediction of cardiac disease.


prediction, cardiac disease, machine learning, algorithms, analysis.


[1] Gandhi, Monika & Singh, Shailendra. (2015). “Predictions in heart disease using techniques of Machine Learning”. 2015 1st International Conference on Futuristic Trends in Computational Analysis and Knowledge Management, ABLAZE 2015. 520-525. 10.1109/ABLAZE.2015.7154917.
[2] Thomas,J.& Princy, R. (2016). “Human heart disease prediction system using Machine Learning techniques”. 1-5. 10.1109/ICCPCT.2016.7530265.
[3] S. Bharti and S. N. Singh, "Analytical study of heart disease prediction comparing with different algorithms," International Conference on Computing, Communication & Automation, Noida, 2015, pp. 78- 82.
[4] Purushottam, & Saxena, Kanak & Sharma, Richa. (2015). “Efficient heart disease prediction system using decision tree”. International Conference on Computing, Communication and Automation, ICCCA 2015. 72-77. 10.1109/CCAA.2015.7148346.
[5] Mat Ghani, Mohd. & Awang, Raflah. (2008). “Intelligent heart disease prediction system using Machine Learning”.8.108 – 115.10.1109/AICCSA.2008.4493524
[6] Sharma Himanshu. “Prediction of Heart Disease using Machine Learning Algorithms: A Survey.” (2017).
[7] Hazra, Animesh & Mandal, Subrata & Gupta, Amit & Mukherjee, Arkomita & Mukherjee, Asmita. (2017). “Heart Disease Diagnosis and Prediction Using Machine Learning : A Review”. Advances in Computational Sciences and Technology. 10. 2137-2159.
[8] V Krishnaiah, G Narsimha and Subhash N Chandra. Article: “Heart Disease Prediction System using Machine Learning Techniques and Intelligent Fuzzy Approach: A Review”. International Journal of Computer Applications 136(2):43- 51, February 2016. Published by Foundation of Computer Science (FCS), NY, USA
[9] Kaur, Ramandeep and Er. Prabhsharn Kaur. “A Review-Heart Disease Forecasting Pattern using Various Machine Learning.” (2016).
[10] Vijayashree, J. & Iyenger, N Ch Sriman Narayana. (2016). “Heart Disease Prediction System Using Machine Learning: A Review”. International Journal of Bio-Science and Bio- Technology. 8. 139-148. 10.14257/ijbsbt.2016.8.4.16.
[11] Yash Panchori, Nikita Agarwal, Aashiya Singhal, Sudhir Busa, "Malaria Parasite Detection using Various Machine Learning Algorithms and Image Processing" SSRG International Journal of Computer Science and Engineering 7.2 , 2020.