Computational methods for breast cancer diagnosis, prognosis, and treatment prediction Saini, Ashish 2014, Computational methods for breast cancer diagnosis, prognosis, and treatment prediction, Ph.D. thesis, School of Information Technology, Deakin University. Attached Files Name Description MIMEType Size Downloads saini-computationalmethods-2014A.pdf Connect to thesis application/pdf 3.40MB 385 Title Computational methods for breast cancer diagnosis, prognosis, and treatment prediction Author Saini, Ashish Institution Deakin University School School of Information Technology Faculty Faculty of Science, Engineering and Built Environment Degree type Research doctorate Degree name Ph.D. Thesis advisor Zhou, Wanlei Hou,Jingyu orcid.org/0000-0002-6403-9786 Date submitted 2014-08 Keyword(s) breast cancer protein interactions diagnotic algorithms prognostic algorithms treatment prediction algorithms Summary The research presented here develops a robust reliability algorithm for the identification of reliable protein interactions that can be incorporated with a gene expression dataset to improve the algorithm performance, and novel breast cancer based diagnostic, prognostic and treatment prediction algorithms, respectively, which take into account the existing issues in order to provide a fair estimation of their performance. Language eng Field of Research 080109 Pattern Recognition and Data Mining 080299 Computation Theory and Mathematics not elsewhere classified Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture) Description of original xix, 227 pages : tables, graphs, diagrams Copyright notice ©The Author. All Rights Reserved Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30073094 Document type: Thesis Collections: Higher degree theses (Open Access) Open Access Collection   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Thu, 07 May 2015, 14:08:54 EST Mon, 11 May 2015, 08:27:12 EST Wed, 24 Jun 2015, 11:00:06 EST Wed, 24 Jun 2015, 11:01:31 EST Wed, 24 Jun 2015, 11:02:43 EST Thu, 09 Mar 2017, 07:08:59 EST Thu, 09 Mar 2017, 08:56:23 EST Wed, 01 Aug 2018, 11:21:50 EST Fri, 07 Sep 2018, 18:55:57 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 299 Abstract Views, 390 File Downloads  -  Detailed Statistics Created: Thu, 07 May 2015, 14:08:40 EST by Kate Percival