Abstract
In the modern world, heart disease is one of the leading causes of death. It has a large global mortality rate, and it now poses a risk to many people’s health. Examination of medical data faces a serious issue with heart disease prediction. It has been demonstrated that machine learning (ML) is useful for aiding in the forecast and making of conclusions drawn from the enormous amount of data that the medical sector produces. In this work, we recommend an innovative method to recognize the large increment in predictive accuracy using ensemble learning techniques. We accurately produce a higher performance level. Machine learning (ML) can offer a practical remedy for decision-making and precise forecasts. The medical sector is demonstrating enormous advancement in the application of machine learning methods. The proposed work suggests using an ensemble machine learning technique to predict cardiac disease. Finally, based on the soft voting ensemble model, our method yielded an accuracy of 89.67%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pouriyeh S, Vahid S, Sannino G, De Pietro G, Arabnia H, Gutierrez J (2017) A comprehensive investigation and comparison of machine learning techniques in the domain of heart disease. In: 2017 IEEE symposium on computers and communications (ISCC), July 2017, IEEE, pp 204–207
Krishnani D, Kumari A, Dewangan A, Singh A, Naik NS (2019) Prediction of coronary heart disease using supervised machine learning algorithms. In: TENCON 2019–2019 IEEE region 10 conference (TENCON), Oct 2019, IEEE, pp 367–372
Pan Y, Fu M, Cheng B, Tao X, Guo J (2020) Enhanced deep learning assisted convolutional neural network for heart disease prediction on the internet of medical things platform. IEEE Access 8:189503–189512
Ganesan M, Sivakumar N (2019) IoT based heart disease prediction and diagnosis model for healthcare using machine learning models. In: 2019 IEEE international conference on system, computation, automation and networking (ICSCAN), Mar 2019, IEEE, pp 1–5
Sowmiya C, Sumitra P (2017) Analytical study of heart disease diagnosis using classification techniques. In: 2017 IEEE international conference on intelligent techniques in control, optimization and signal processing (INCOS), Mar 2017, IEEE, pp 1–5
Sultana M, Haider A, Uddin MS (2016) Analysis of data mining techniques for heart disease prediction. In: 2016 3rd international conference on electrical engineering and information communication technology (ICEEICT), Sep 2016, IEEE, pp 1–5
Amin SU, Agarwal K, Beg R (2013) Genetic neural network based data mining in prediction of heart disease using risk factors. In: 2013 IEEE conference on information and communication technologies, Apr 2013, IEEE, pp 1227–1231
Ferdousi R, Hossain MA, El Saddik A (2021) Early-stage risk prediction of non-communicable disease using machine learning in health CPS. IEEE Access 9:96823–96837
Ali L, Rahman A, Khan A, Zhou M, Javeed A, Khan JA (2019) An automated diagnostic system for heart disease prediction based on ${\chi^{2}} $ statistical model and optimally configured deep neural network. IEEE Access 7:34938–34945
Mohan S, Thirumalai C, Srivastava G (2019) Effective heart disease prediction using hybrid machine learning techniques. IEEE Access 7:81542–81554
Thomas J, Princy RT (2016) Human heart disease prediction system using data mining techniques. In: 2016 international conference on circuit, power and computing technologies (ICCPCT), Mar 2016, IEEE, pp 1–5
Khan MA (2020) An IoT framework for heart disease prediction based on MDCNN classifier. IEEE Access 8:34717–34727
Fitriyani NL, Syafrudin M, Alfian G, Rhee J (2020) HDPM: an effective heart disease prediction model for a clinical decision support system. IEEE Access 8:133034–133050
Bashir S, Khan ZS, Khan FH, Anjum A, Bashir K (2019) Improving heart disease prediction using feature selection approaches. In: 2019 16th international Bhurban conference on applied sciences and technology (IBCAST), Jan 2019, IEEE, pp 619–623
Chen AH, Huang SY, Hong PS, Cheng CH, Lin EJ (2011) HDPS: heart disease prediction system. In: 2011 computing in cardiology, Sept 2011, IEEE, pp 557–560
Gavhane A, Kokkula G, Pandya I, Devadkar K (2018) Prediction of heart disease using machine learning. In: 2018 second international conference on electronics, communication and aerospace technology (ICECA), Mar 2018, IEEE, pp 1275–1278
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gavali, P.R., Bhosale, S.A., Sangar, N.A., Patil, S.R. (2023). Ensemble Learning Approach for Heart Disease Prediction. In: Shukla, P.K., Mittal, H., Engelbrecht, A. (eds) Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4577-1_4
Download citation
DOI: https://doi.org/10.1007/978-981-99-4577-1_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-4576-4
Online ISBN: 978-981-99-4577-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)