Sign inSubmit

Journal of Computer Science

ISSN 1549-3636 (print)eISSN 1552-6607 (online) Open access
Sign up for alertsSubmit manuscript
computersciencejournal.org is not ours. This journal is published only at thescipub.com/jcs. Report a suspicious emailcomputersciencejournal.org is not ours · Report
ArticleMetrics
Research Article · Open access · Published 4 December 2024

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 & Konduru Kranthi Kumar7

Journal of Computer Science, Volume 21, Issue 1, pp. 71–77 · doi.org/10.3844/jcssp.2025.71.77

5,227 accesses2,647 downloads1 citations (Crossref)Metrics
Cite Check for updates

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.

Licence and reuse

Open access. This article is licensed under a Creative Commons Attribution 4.0 International Licence (CC BY 4.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

How to reuse this article

Responses (0)

Have a comment on this research? Sign in to respond. Responses are moderated and published with your name and affiliation; the authors are invited to reply. How we use your dataWrite a response

About this article

Cite this article

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

Licence
CC BY 4.0
Issue
Volume 21, Issue 1
Policies
Editorial independenceUse of generative AIData availabilityAppeals and complaints
Version
Version of record
A Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired AlgorithmsJournal of Computer Science · Volume 21, Issue 1 · pp. 71–77 · CC BY 4.0Download