Parsimonious evolutionary-based model development for detecting artery disease

Jalali, Seyed Mohammad Jafar, Khosravi, Abbas, Alizadehsani, Roohallah, Salaken, Syed Moshfeq, Kebria, Parham Mohsenzadeh, Puri, Rishi and Nahavandi, Saeid 2019, Parsimonious evolutionary-based model development for detecting artery disease, in ICIT 2019 : Proceedings of the IEEE International Conference on Industrial Technology, IEEE, Piscataway, N.J., pp. 800-805, doi: 10.1109/ICIT.2019.8755107.

Attached Files
Name Description MIMEType Size Downloads

Title Parsimonious evolutionary-based model development for detecting artery disease
Author(s) Jalali, Seyed Mohammad Jafar
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Alizadehsani, Roohallah
Salaken, Syed MoshfeqORCID iD for Salaken, Syed Moshfeq orcid.org/0000-0001-8632-2665
Kebria, Parham MohsenzadehORCID iD for Kebria, Parham Mohsenzadeh orcid.org/0000-0001-7049-928X
Puri, Rishi
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Conference name Industrial Technology. Conference (2019 : Melbourne, Victoria)
Conference location Melbourne, Victoria
Conference dates 13-15 Feb. 2019
Title of proceedings ICIT 2019 : Proceedings of the IEEE International Conference on Industrial Technology
Publication date 2019
Start page 800
End page 805
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) coronary artery disease
Data Mining
Evolutionary Algorithm
GEP
GA-ENN
Feature Selection
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
NEURAL-NETWORKS
CLASSIFICATION
PREDICTION
ISBN 9781538663769
Language eng
DOI 10.1109/ICIT.2019.8755107
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30128307

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 7 times in TR Web of Science
Scopus Citation Count Cited 8 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 56 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 29 Jul 2019, 15:28:55 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.