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NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease

Abdar, Moloud, Acharya, U. Rajendra, Sarrafzadegan, Nizal and Makarenkov, Vladimir 2019, NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease, IEEE Access, vol. 7, pp. 167605-167620, doi: 10.1109/ACCESS.2019.2953920.


Title NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease
Author(s) Abdar, MoloudORCID iD for Abdar, Moloud orcid.org/0000-0002-3059-6357
Acharya, U. Rajendra
Sarrafzadegan, Nizal
Makarenkov, Vladimir
Journal name IEEE Access
Volume number 7
Start page 167605
End page 167620
Total pages 16
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2019-01-01
ISSN 2169-3536
Keyword(s) Coronary artery disease (CAD)
machine learning
ensemble learning
nested ensemble (NE) model
genetic algorithm
Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
IMMUNE RECOGNITION SYSTEM
DATA MINING TECHNIQUES
HEART-DISEASE
ECG SIGNALS
NEURAL-NETWORKS
CLASSIFICATION
PREDICTION
PERFORMANCE
ALGORITHM
MODEL
Language eng
DOI 10.1109/ACCESS.2019.2953920
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30134236

Document type: Journal Article
Collections: Open Access Collection
Deputy Vice-Chancellor Research Group
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Created: Thu, 30 Jan 2020, 14:35:59 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.