Model uncertainty quantification for diagnosis of each main coronary artery stenosis Alizadehsani, Roohallah, Roshanzamir, Mohamad, Abdar, Moloud, Beykikhoshk, Adham, Zangooei, Mohammad Hossein, Khosravi, Abbas, Nahavandi, Saeid, Tan, Ru San and Acharya, U. Rajendra 2019, Model uncertainty quantification for diagnosis of each main coronary artery stenosis, Soft Computing, pp. 1-12, doi: 10.1007/s00500-019-04531-0. Attached Files Name Description MIMEType Size Downloads Title Model uncertainty quantification for diagnosis of each main coronary artery stenosis Author(s) Alizadehsani, Roohallah Roshanzamir, Mohamad Abdar, Moloud Beykikhoshk, Adham Zangooei, Mohammad Hossein Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Tan, Ru San Acharya, U. Rajendra Journal name Soft Computing Start page 1 End page 12 Total pages 12 Publisher Springer Place of publication Berlin, Germany Publication date 2019 ISSN 1432-7643 1433-7479 Keyword(s) Data mining Machine learning Coronary artery disease SVM Gini index LAD Feature selection Notes In press article Language eng DOI 10.1007/s00500-019-04531-0 Indigenous content off Field of Research 0102 Applied Mathematics 0801 Artificial Intelligence and Image Processing 1702 Cognitive Sciences HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2019, Springer-Verlag GmbH Germany, part of Springer Nature. Persistent URL http://hdl.handle.net/10536/DRO/DU:30133093 Document type: Journal Article Collection: Institute for Intelligent Systems Research and Innovation (IISRI) 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, 11 Dec 2019, 13:20:23 EST Thu, 12 Dec 2019, 04:00:17 EST Thu, 12 Dec 2019, 05:04:05 EST Thu, 09 Jan 2020, 13:24:39 EST Thu, 09 Jan 2020, 13:32:22 EST Thu, 09 Jan 2020, 13:33:06 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 29 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Wed, 11 Dec 2019, 13:20:23 EST

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