Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection Kipli, Kuryati and Kouzani, Abbas Z. 2015, Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection, International journal of computer assisted radiology and surgery, vol. 10, no. 7, pp. 1003-1016, doi: 10.1007/s11548-014-1130-9. Attached Files Name Description MIMEType Size Downloads Title Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection Author(s) Kipli, Kuryati Kouzani, Abbas Z. orcid.org/0000-0002-6292-1214 Journal name International journal of computer assisted radiology and surgery Volume number 10 Issue number 7 Start page 1003 End page 1016 Total pages 14 Publisher Springer Place of publication Berlin, Germany Publication date 2015-07 ISSN 1861-6429 Keyword(s) Brain sMRI data Degree of contribution Depression detection Ensemble Feature selection Volumetric features Summary Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression. Language eng DOI 10.1007/s11548-014-1130-9 Field of Research 090609 Signal Processing Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2014, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30069943 Document type: Journal Article Collection: School of Engineering Related Links Link Description Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system 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 Mon, 23 Feb 2015, 14:45:23 EST Mon, 23 Feb 2015, 14:46:01 EST Tue, 24 Feb 2015, 04:00:49 EST Tue, 24 Feb 2015, 05:07:47 EST Wed, 04 Mar 2015, 13:29:12 EST Wed, 04 Mar 2015, 13:32:13 EST Fri, 22 May 2015, 11:47:55 EST Mon, 25 May 2015, 08:13:32 EST Wed, 14 Oct 2015, 14:14:46 EST Thu, 16 Feb 2017, 14:13:07 EST Fri, 21 Apr 2017, 11:10:17 EST Filtered Full Citation counts:   Cited 1 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 221 Abstract Views, 3 File Downloads  -  Detailed Statistics Created: Mon, 23 Feb 2015, 14:46:01 EST

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