Vol. 1 No. 1 (2023): Jan/June - Issue - 01
Articles

Obtaining Better Accuracy Using Fusion of Two Machine Learning Algorithms for Prediction of Heart Attack

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  • Soumyashree M,
  • A R S Bhaargav,
  • Prashanth B K,
  • S Ajith Kumar Reddy
Soumyashree M
Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India
A R S Bhaargav
School of Computer Science and Engineering, REVA University, Bangalore, India
Prashanth B K
School of Computer Science and Engineering, REVA University, Bangalore, India
S Ajith Kumar Reddy
School of Computer Science and Engineering, REVA University, Bangalore, India
DOI: https://doi.org/10.5281/zenodo.8344749

Published 2023-09-14

Keywords

  • Decision Tree,
  • Random Forest,
  • Hybrid Model,
  • Model Ensemble,
  • SDLC model like spiral V and C,
  • Graphical User Interface,
  • Django
    • ...More
    Less

How to Cite

Soumyashree M, A R S Bhaargav, Prashanth B K, & S Ajith Kumar Reddy. (2023). Obtaining Better Accuracy Using Fusion of Two Machine Learning Algorithms for Prediction of Heart Attack. Milestone Transactions on Medical Technometrics, 1(1), 45–52. https://doi.org/10.5281/zenodo.8344749

Abstract

There are numerous terms and labels for heart illness. The effects and processes of a cardiac condition can be very complicated, especially for those who are experiencing them themselves or through a loved one of the victim. Therefore, the goal of this paper is to understand why heart disease plays a factor in nearly half of all reported fatalities in society. This paper will start by outlining the fundamental concepts of what a cardiac illness is and how people typically view it. Additionally, this paper will explore the most prevalent risk factors for developing heart disease, and we'll do it by employing ML algorithms using a hybrid model.
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