Cardiovascular Disease Long-Term Care Risk Prediction by Claims Data Analysis Using Machine Learning

Sourabh Pawar, Pranav More; Tejas Pawar; Prof. Priti Rathod

doi:10.32628/IJSRSET2411222

Authors

Sourabh Pawar, Pranav More Computer Engineering Department, Ajeenkya Dr. D.Y Patil SOET, Pune, Maharashtra, India Author
Tejas Pawar Computer Engineering Department, Ajeenkya Dr. D.Y Patil SOET, Pune, Maharashtra, India Author
Prof. Priti Rathod Computer Engineering Department, Ajeenkya Dr. D.Y Patil SOET, Pune, Maharashtra, India Author

DOI:

https://doi.org/10.32628/IJSRSET2411222

Keywords:

Cardiovascular Disease Prediction, Healthcare, Machine Learning

Abstract

Heart complaint is a major global health concern, especially in prognosticating cardiovascular issues. Machine literacy (ML) and the Internet of effects (IoT) offer new ways to dissect healthcare data. still, current exploration lacks depth in using ML for heart complaint vaticination. To fill this gap, we propose a unique system that uses ML to identify crucial features for better heart complaint vaticination delicacy. Our model combines colorful features and bracket ways to achieve an delicacy of 88.7 in prognosticating heart complaint, with the cold-blooded arbitrary timber and direct model (HRFLM) proving particularly effective. This study advances heart complaint discovery by integrating ML and IoT technologies.

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References

Shadman Nashif, Md. Rakib Raihan, Md. Rasedul Islam and Mohammad Hasan Imam,” Heart Disease Detection by Using

Amin Ul Haq and Jian Ping Li , Muhammad Hammad Memon , Shah Nazir , and Ruinan Sun , “A Hybrid Intelligent System Framework for the Prediction of Heart Disease Using Machine Learning Algorithms”, Hindawi Mobile Information Systems Volume 2018, Article ID 3860146, 21 pages . DOI: https://doi.org/10.1155/2018/3860146

Youness Khourdifi and Mohamed Bahajm researched ,” Heart Disease Prediction and Classification Using Machine Learning Algorithms Optimized by Particle Swarm Optimization and Ant Colony Optimization”, International Journal of Intelligent Engineering and Systems, Vol.12, No.1, 2019 DOI: 10.22266/ijies2019.0228.24. DOI: https://doi.org/10.22266/ijies2019.0228.24

Li Yang, Haibin Wu, Xiaoqing Jin, and Pinpin Zheng4 et al., “Study of cardiovascular disease prediction model based on random forest in eastern China “ Scientific Reports (2020) 10:5245 DOI: https://doi.org/10.1038/s41598-020-62133-5

S. Mohan, C. Thirumalai and G. Srivastava, have further studied "Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques," in IEEE Access, vol. 7, pp. 81542-81554, 2019, doi: 10.1109/ACCESS.2019.2923707 DOI: https://doi.org/10.1109/ACCESS.2019.2923707