Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease

Zomorodi-moghadam, Mariam, Abdar, Moloud, Davarzani, Zohreh, Zhou, Xujuan, Pławiak, Pawel and Acharya, U.Rajendra 2019, Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease, Expert systems, pp. 1-17, doi: 10.1111/exsy.12485.

Attached Files
Name Description MIMEType Size Downloads

Title Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease
Author(s) Zomorodi-moghadam, Mariam
Abdar, MoloudORCID iD for Abdar, Moloud orcid.org/0000-0002-3059-6357
Davarzani, Zohreh
Zhou, Xujuan
Pławiak, Pawel
Acharya, U.Rajendra
Journal name Expert systems
Start page 1
End page 17
Total pages 17
Publisher Wiley
Place of publication Chichester, Eng.
Publication date 2019
ISSN 0266-4720
1468-0394
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Computer Science
classification
coronary artery disease (CAD)
hybrid particle swarm optimization
rule discovery
DEEP LEARNING-MODEL
NEURAL-NETWORK
EVOLUTIONARY ALGORITHMS
DECISION-MAKING
Notes Early View Article
Language eng
DOI 10.1111/exsy.12485
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
1702 Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30134228

Document type: Journal Article
Collection: Institute for Intelligent Systems Research and Innovation (IISRI)
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in TR Web of Science
Scopus Citation Count Cited 6 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 28 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Thu, 30 Jan 2020, 14:34:01 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.