A Literature Review for Detection and Projection of Cardiovascular Disease Using Machine Learning


  • Sumati Baral Sri Sri University image/svg+xml
  • Suneeta Satpathy Siksha O Anusandhan University image/svg+xml
  • Dakshya Prasad Pati Trident Academy of Creative Technology
  • Pratiti Mishra Trident Academy of Creative Technology
  • Lalmohan Pattnaik Sri Sri University image/svg+xml




Support Vector Machine, SVM, Naive Bayes, K-Nearest Neighbor, Coronary artery disease, Arterial pressure, Data Mining, Decision tree


The heart is a vital organ that is indispensable in ensuring the general health and welfare of individuals. Cardiovascular diseases (CVD) are the major health concern worldwide and a leading cause of death, leaving behind diabetes and cancer. To deal with the problem, it is essential for early detection and prediction of CVDs, which can significantly reduce morbidity and mortality rates. Computer-aided techniques facilitate physicians in the diagnosis of many heart disorders, such as valve dysfunction, heart failure, etc. Living in an "information age," every day million bytes of data are generated, and we can turn these data into knowledge for clinical investigation using the technique of data mining. Machine learning algorithms have shown promising results in predicting heart disease based on different risk parameter. In this study, for the purpose of predicting CVDs, our aim is to appraise and examine the outputs generated by machine learning algorithms including support vector machines, artificial neural network, logistic regression, random forest and decision trees.This literature survey highlights the correctness of different machine learning algorithms in forecasting heart problem and can be used as a basis for building a Clinical decision-making aid to detect and prevent heart disease at an early stage.


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A. Javeed, S. Zhou, L. Yongjian, I. Qasim, A. Noor, and R. Nour, “An Intelligent Learning System Based on Random Search Algorithm and Optimized Random Forest Model for Improved Heart Disease Detection,” IEEE Access, vol. 7, pp. 180235– 180243, 2019, DOI: 10.1109/ACCESS.2019.2952107. DOI: https://doi.org/10.1109/ACCESS.2019.2952107

Mr.Santhana Krishnan.J, Dr.Geetha.S,” Prediction of Heart Disease Using Machine Learning Algorithms”,2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT), DOI:10.1109/ICIICT1.2019.8741465. DOI: https://doi.org/10.1109/ICIICT1.2019.8741465

Aditi Gavhane, Gouthami Kokkula, Isha Pandya, Kailas Devadkar “Prediction of Heart Disease Using Machine Learning”, International conference on Electronics, Communication and Aerospace Technology (ICECA 2018) IEEE Conference Record # 42487; IEEEXplore ISBN:978-1-5386-0965-1 DOI: 10.1109/ICECA.2018.8474922 DOI: https://doi.org/10.1109/ICECA.2018.8474922

Devansh Shah, Samir Patel, Santosh Kumar Bharti 2020 “Heart Disease Prediction using Machine Learning Techniques” DOI: https://doi.org/10.1007/s42979-020-00365-y

Archana Singh, Rakesh Kumar 2020 International Conference on Electrical and Electronics Engineering (ICE3), DOI: 10.1109/ICE348803.2020.9122958 DOI: https://doi.org/10.1109/ICE348803.2020.9122958

Apurb Rajdhan, Avi Agarwal , Milan Sai “ Heart Disease Prediction using Machine Learning” May 2020 International Journal of Engineering and Technical Research V9(04) DOI:10.17577/IJERTV9IS040614 DOI: https://doi.org/10.17577/IJERTV9IS040614

Goel, Rati, “Heart Disease Prediction Using Various Algorithms of Machine Learning” (July 12, 2021). Proceedings of the International Conference on Innovative Computing & Communication (ICICC) 2021, Available at SRN: https://ssrn.com/abstract=3884968 or http://dx.doi.org/10.2139/ssrn.3884968 DOI: https://doi.org/10.2139/ssrn.3884968

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Apurv Garg, Bhartendu Sharma and Rijwan Khan “heart disease prediction using machine learning techniques” January 2021 IOP Conference Series Materials Science and Engineering 1022(1):012046 DOI:10.1088/1757-899X/1022/1/012046. DOI: https://doi.org/10.1088/1757-899X/1022/1/012046

Md. Mahbubur Rahman, Morshedur Rahman Rana, Md. Nur-A-Alam, Md. Saikat Islam Khan, Khandaker Mohammad Mohi Uddin “A web-based heart disease prediction system using machine learning Algorithms “June 2022

Heart Attack Prediction Using Machine Learning Algorithms Manjula P, Aravind U R, Darshan M V, Halaswamy M H, Hemanth E International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 Special Issue – 2022

Pavan kumar Tadiparthi “Heart Disease Prediction Using Machine Learning Algorithms: A Systematic Survey” 2022 Journal International Journal of Computer Science and Mobile Computing Volume 11 Issue 6 Pages 129-136 DOI: https://doi.org/10.47760/ijcsmc.2022.v11i06.010

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Heart Disease Prediction using Machine Learning Techniques by Reldean Williams, Thokozani Shongwe, Ali N. Hasan, Vikash Rameshar DOI:10.1109/ICDABI53623.2021.9655783 Conference: 2021 International Conference on Data Analytics for Business and Industry (ICDABI)

S. F. Weng, J. Reps, J. Kai, J. M. Garibaldi, and N. Qureshi. “Can machine learning improve cardio-vascular risk prediction using routine clinical data”, 2017. DOI: https://doi.org/10.1371/journal.pone.0174944

A. Kishore, A. Kumar, K. Singh, M. Punia, and Y. Hambir, “Heart attack prediction using deep learning,” Department of Computer Engineering., Army Institute of Technology, Pune, Maharashtra Professor, 2018.

Avinash Golande, Pavan Kumar T,” Heart Disease Prediction Using Effective Machine Learning Techniques”, InternationalJournal of Recent Technology and Engineering (IJRTE) ISSN:2277-3878, Volume-8, Issue-1S4, June 2019.

V.V. Ramalingam, Ayantan Dandapath, M Karthik Raja,” Heart disease prediction using machine learning techniques: a survey”, International Journal of Engineering & Technology, 7 (2.8) (2018) 684-687. DOI: https://doi.org/10.14419/ijet.v7i2.8.10557

M. Nikhil Kumar, K. V. S. Koushik, K. Deepak.(2019). “Prediction of Heart Diseases Using Data Mining and Machine Learning Algorithms and Tools” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, IJSRCSEIT.

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S. Bashir, Z. S. Khan, F. H. Khan, A. Anjum, and K. Bashir, “Improving heart disease prediction using feature selection approaches,” in Proceedings of the 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST), pp. 619–623, Islamabad, Pakistan, January 2019. View at: Publisher Site | Google Scholar DOI: https://doi.org/10.1109/IBCAST.2019.8667106

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Arsalan Khan, Moiz Qureshi,Muhammad Daniyal,and Kassim Tawiah A Novel Study on Machine Learning Algorithm-Based Cardiovascular Disease Prediction Volume 2023 | Article ID 1406060 | https://doi.org/10.1155/2023/1406060 DOI: https://doi.org/10.1155/2023/1406060

M. Kavitha, G. Gnaneswar, R. Dinesh, Y. R. Sai, and R. S. Suraj, “Heart disease prediction using hybrid machine learning model,” in Proceedings of the 2021 6th International Conference on Inventive Computation Technologies (ICICT), pp. 1329–1333, Coimbatore, India, January 2021. View at: Publisher Site | Google Scholar DOI: https://doi.org/10.1109/ICICT50816.2021.9358597

Chintan M. Bhatt , Parth Patel , Tarang Ghetia and Pier Luigi Mazzeo Effective Heart Disease Prediction Using Machine Learning Techniques 2023, Volume 16 Issue 2 https://doi.org/10.3390/a16020088 DOI: https://doi.org/10.3390/a16020088

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How to Cite

S. Baral, S. Satpathy, D. P. Pati, P. Mishra, and L. Pattnaik, “A Literature Review for Detection and Projection of Cardiovascular Disease Using Machine Learning ”, EAI Endorsed Trans IoT, vol. 10, Mar. 2024.