CARDIOVASCULAR DISEASE DETECTION USING OPTIMAL FEATURE SELECTION - Couverture souple

Gade, Mary Swarna Latha; K, Laxmi Narayanamma

 
9786208225797: CARDIOVASCULAR DISEASE DETECTION USING OPTIMAL FEATURE SELECTION
Couverture souple
ISBN 10 : 6208225795 ISBN 13 : 9786208225797
Editeur : LAP LAMBERT Academic Publishing, 2025

Synopsis

Cardiovascular disease (CVD) remains a leading cause of death globally, emphasizing the need for accurate early detection. This study presents a machine learning-based framework for CVD detection using ECG signals, focusing on enhanced feature selection. The system integrates Fast Correlation-Based Filter (FCBF), Minimum Redundancy Maximum Relevance (mRMR), Relief, and Particle Swarm Optimization (PSO) to identify the most relevant and non-redundant features. FCBF removes redundant data, mRMR selects key relevant features, Relief ranks features based on their class-distinguishing power, and PSO optimizes the final feature set. Classification is performed using Extra Trees and Random Forest classifiers, known for high accuracy and resistance to overfitting. The combined model achieved a 100% accuracy rate across diverse datasets, outperforming existing methods and demonstrating superior performance in feature selection and classification. This framework holds strong potential to improve early CVD diagnosis and enhance clinical decision-making.

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Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2025
Langue
anglais
ISBN 10 
6208225795
ISBN 13 
9786208225797
Reliure
Broché
Nombre de pages
56
Coordonnées du fabricant
non disponible
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