A new machine learning technique for an accurate diagnosis of coronary artery disease

Abdar, Moloud, Książek, Wojciech, Acharya, U Rajendra, Tan, Ru-San, Makarenkov, Vladimir and Pławiak, Pawel 2019, A new machine learning technique for an accurate diagnosis of coronary artery disease, Computer Methods and Programs in Biomedicine, vol. 179, pp. 1-11, doi: 10.1016/j.cmpb.2019.104992.

Attached Files
Name Description MIMEType Size Downloads

Title A new machine learning technique for an accurate diagnosis of coronary artery disease
Author(s) Abdar, MoloudORCID iD for Abdar, Moloud orcid.org/0000-0002-3059-6357
Książek, Wojciech
Acharya, U Rajendra
Tan, Ru-San
Makarenkov, Vladimir
Pławiak, Pawel
Journal name Computer Methods and Programs in Biomedicine
Volume number 179
Article ID 104992
Start page 1
End page 11
Total pages 11
Publisher Elsevier
Place of publication Shannon, Ireland
Publication date 2019-10
ISSN 0169-2607
Keyword(s) Science & Technology
Technology
Life Sciences & Biomedicine
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
Engineering, Biomedical
Medical Informatics
Computer Science
Engineering
Coronary artery disease (CAD)
Machine learning
Normalization
Genetic algorithm
Particle swarm optimization
Feature selection
Classification
MYOCARDIAL-INFARCTION
NEURAL-NETWORK
HEART-DISEASE
ECG SIGNALS
COMPUTED-TOMOGRAPHY
AUTOMATED DETECTION
COGNITIVE ANALYSIS
PARTICLE SWARM
Language eng
DOI 10.1016/j.cmpb.2019.104992
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30134109

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 20 times in TR Web of Science
Scopus Citation Count Cited 27 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 10 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Thu, 30 Jan 2020, 13:36:16 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.