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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

A Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired Algorithms

Indira Priyadarsini1, I.S. Siva Rao2, P. Swetha3, T. Anuradha4, V. Sujatha5, B. Divya6 and Konduru Kranthi Kumar7
  • 1 Department of Data Science & Cyber security, AVNIET, Koheda Road, Hyderabad, India
  • 2 Department of Computer Science and Systems Engineering Andhra University Visakhapatnam, India
  • 3 Department of Artificial Intelligence & Data Science, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India
  • 4 Department of CSBS, R.V.R & J.C College of Engineering, Chowdavaram, A.P, India
  • 5 Department of Computer Applications, R.V.R & J.C College of Engineering, Chowdavaram, A.P, India
  • 6 Department of Artificial Intelligence and Data Science, Karpaga Vinayaga College of Engineering and Technology, Tamil Nadu, India
  • 7 Department of Information Technology, Vasireddy Venkatadri Institute of Technology, Guntur, A.P, India

Abstract

This study presents a novel approach for early prediction of heart disease using bio-inspired optimization algorithms to select and optimize features. The proposed approach utilizes a Genetic Algorithm (GA), Bat Algorithm (BA), Bee Algorithm (BA), and Ant Colony Optimization (ACO) to optimize a set of four features for improved prediction accuracy. The optimization process aims to identify the most relevant features from a large feature set, enhancing the performance of the machine learning model used for prediction. Experimental results on benchmark heart disease datasets demonstrate the effectiveness of the proposed approach, achieving significant improvements in prediction accuracy compared to traditional feature selection methods. The findings highlight the potential of bio-inspired optimization algorithms in enhancing the predictive capabilities of machine learning models for early detection of heart disease.

Journal of Computer Science
Volume 21 No. 1, 2025, 71-77

DOI: https://doi.org/10.3844/jcssp.2025.71.77

Submitted On: 4 March 2024 Published On: 4 December 2024

How to Cite: Priyadarsini, I., Rao, I. S., Swetha, P., Anuradha, T., Sujatha, V., Divya, B. & Kumar, K. K. (2025). A Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired Algorithms. Journal of Computer Science, 21(1), 71-77. https://doi.org/10.3844/jcssp.2025.71.77

Open AccessCopyright: © 2025 Indira Priyadarsini, I.S. Siva Rao, P. Swetha, T. Anuradha, V. Sujatha, B. Divya and Konduru Kranthi Kumar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Heart Disease Prediction
  • Bio-Inspired Optimization Algorithms
  • Genetic Algorithm
  • Bat Algorithm
  • Bee Algorithm
  • Ant Colony Optimization
  • Feature Selection
  • Machine Learning