Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries Alizadehsani, Roohallah, Hosseini, Mohammad Javad, Khosravi, Abbas, Khozeimeh, Fahime, Roshanzamir, Mohamad, Sarrafzadegan, Nizal and Nahavandi, Saeid 2018, Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries, Computer methods and programs in biomedicine, vol. 162, pp. 119-127, doi: 10.1016/j.cmpb.2018.05.009. Attached Files Name Description MIMEType Size Downloads Title Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries Author(s) Alizadehsani, Roohallah Hosseini, Mohammad Javad Khosravi, Abbas orcid.org/0000-0001-6927-0744 Khozeimeh, Fahime Roshanzamir, Mohamad Sarrafzadegan, Nizal Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Journal name Computer methods and programs in biomedicine Volume number 162 Start page 119 End page 127 Total pages 9 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2018-08 ISSN 1872-7565 Keyword(s) Coronary artery disease Feature selection Naive Bayes and C4.5 classifiers Support vector machine Science & Technology Technology Life Sciences & Biomedicine Computer Science, Interdisciplinary Applications Computer Science, Theory & Methods Engineering, Biomedical Medical Informatics Computer Science Engineering BREAST-CANCER CLASSIFICATION SUPPORT VECTOR MACHINES HEART-VALVE DISEASES INTRAVASCULAR ULTRASOUND AUTOMATED DIAGNOSIS NONLINEAR FEATURES COMPONENT ANALYSIS NEURAL-NETWORKS DATA SETS SYSTEM Language eng DOI 10.1016/j.cmpb.2018.05.009 Field of Research 080109 Pattern Recognition and Data Mining 0903 Biomedical Engineering Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2018, Elsevier Persistent URL http://hdl.handle.net/10536/DRO/DU:30109410 Document type: Journal Article 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 Tue, 12 Jun 2018, 15:58:03 EST Wed, 13 Jun 2018, 05:06:27 EST Wed, 13 Jun 2018, 08:09:18 EST Sat, 21 Jul 2018, 02:30:06 EST Wed, 25 Jul 2018, 06:05:31 EST Thu, 26 Jul 2018, 13:03:36 EST Thu, 26 Jul 2018, 13:07:48 EST Filtered Full Citation counts:   Cited 19 times in TR Web of Science Cited 34 times in Scopus Search Google Scholar Access Statistics: 282 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 12 Jun 2018, 15:58:02 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.