ItemArticle

HEART FAILURE DETECTION USING OPTIMIZATION ALGORITHMS

Title
HEART FAILURE DETECTION USING OPTIMIZATION ALGORITHMS
Creator
Kumar, Amaravarapu Pramod; Macha, Yuvaraj; Kumar, A. Siva; Sekhar, Buna; Krishnapriya, Singamaneni; Chanti, S.
Description
Heart failure (HF) remains a significant global health challenge, requiring early and precise detection to improve clinical outcomes and reduce mortality rates. Traditional diagnostic approaches often fail to capture the complexity of HF pathophysiology, necessitating advanced computational methods for accurate prediction. In this study, we propose a novel optimized Stacked Support Vector Machine (S-SVM) framework, integrating multiple SVM classifiers with diverse kernel functions to enhance predictive accuracy. A genetic algorithm (GA) is employed to fine-tune hyperparameters, ensuring model robustness and generalizability across patient populations. The model is rigorously evaluated on the UCI Heart Failure Clinical Records Dataset and the Framingham Heart Study Dataset, demonstrating superior performance in accuracy (95.7%), precision (0.90), recall (0.87), and AUC (0.96) compared to conventional machine learning techniques. The proposed system effectively balances computational efficiency with clinical interpretability, making it a promising tool for early-stage HF detection and risk stratification. This research advances the intersection of machine learning and cardiovascular diagnostics, offering a scalable and adaptive solution for real-world healthcare applications. Little Lion Scientific.
Source
Journal of Theoretical and Applied Information Technology;Volume;103;Issue;7;pp.2594-2611
Date
01-01-2025
Publisher
Little Lion Scientific
Subject
Cardiovascular Diagnostics; Clinical DeciSion Support; Genetic Algorithm; Heart Failure Prediction; Machine Learning; Stacked SVM
Coverage
Kumar A.P., CSE-(Cys,DS) and AI & DS, VNR Vignana Jyothi Institute of ENgineering and Technology, Bachupally, Hyderbad, India; Macha Y., Department of Mathematics, Matrusri Engineering College, Telengana, Hyderbad, India; Kumar A.S., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation (KLEF), KL University, Vijayawada Campus, Green Fields, Andhra Pradesh, Vaddeswaram, India; Sekhar B., CSE, CMR Institute of Technology, Kandlakoya,Medchal, Telengana, Hyderbad, India; Krishnapriya S., CSE-(Cys,DS) and AI & DS, VNR Vignana Jyothi Institute of ENgineering and Technology, Telenagan, Hyderbad, India; Chanti S., Department of Computer Science, Christ University, Karnataka, Bangaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 19928645;
Format
online
Language
English
Type
Article

Citation

Kumar, Amaravarapu Pramod; Macha, Yuvaraj; Kumar, A. Siva; Sekhar, Buna; Krishnapriya, Singamaneni; Chanti, S., “HEART FAILURE DETECTION USING OPTIMIZATION ALGORITHMS,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/23787.

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