An efficient neuroevolution approach for heart disease detection Jalali, Seyed Mohammad Jafar, Karimi, Mina, Khosravi, Abbas and Nahavandi, Saeid 2019, An efficient neuroevolution approach for heart disease detection, in SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, IEEE, Piscataway, N.J., pp. 3771-3776, doi: 10.1109/SMC.2019.8913997. Attached Files Name Description MIMEType Size Downloads Title An efficient neuroevolution approach for heart disease detection Author(s) Jalali, Seyed Mohammad Jafar Karimi, Mina Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Systems, Man and Cybernetics. Conference (2019 : Bari, Italy) Conference location Bari, Italy Conference dates 06-09 Oct. 2019 Title of proceedings SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics Publication date 2019 Start page 3771 End page 3776 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) Science & Technology Technology Computer Science, Cybernetics Computer Science, Information Systems Computer Science MOTION ERROR ISBN 9781728145693 ISSN 1062-922X Language eng DOI 10.1109/SMC.2019.8913997 Indigenous content off Field of Research 080110 Simulation and Modelling HERDC Research category E1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30137003 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 13 May 2020, 14:38:13 EST Thu, 14 May 2020, 05:02:04 EST Thu, 14 May 2020, 06:04:48 EST Thu, 14 May 2020, 15:11:14 EST Thu, 14 May 2020, 15:11:48 EST Filtered Full Citation counts:   Cited 5 times in TR Web of Science Cited 11 times in Scopus Search Google Scholar Access Statistics: 85 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Wed, 13 May 2020, 14:38:13 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.