Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach

Nasarian, Elham, Abdar, Moloud, Fahami, Mohammad Amin, Alizadehsani, Roohallah, Hussain, Sadiq, Basiri, Mohammad Ehsan, Zomorodi-Moghadam, Mariam, Zhou, Xujuan, Pławiak, Pawel, Acharya, U. Rajendra, Tan, Ru-San and Sarrafzadegan, Nizal 2020, Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach, Pattern recognition letters, vol. 133, pp. 33-40, doi: 10.1016/j.patrec.2020.02.010.

Attached Files
Name Description MIMEType Size Downloads

Title Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach
Author(s) Nasarian, Elham
Abdar, MoloudORCID iD for Abdar, Moloud orcid.org/0000-0002-3059-6357
Fahami, Mohammad Amin
Alizadehsani, Roohallah
Hussain, Sadiq
Basiri, Mohammad Ehsan
Zomorodi-Moghadam, Mariam
Zhou, Xujuan
Pławiak, Pawel
Acharya, U. Rajendra
Tan, Ru-San
Sarrafzadegan, Nizal
Journal name Pattern recognition letters
Volume number 133
Start page 33
End page 40
Total pages 8
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2020-05
ISSN 0167-8655
Keyword(s) Machine learning
Data mining
Heart disease
Coronary artery disease
Feature selection
Language eng
DOI 10.1016/j.patrec.2020.02.010
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
1702 Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30137755

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 2 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 10 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 01 Jun 2020, 12:55:37 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.