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Building stable predictive models for healthcare applications: a data-driven approach

Kamkar, Iman 2016, Building stable predictive models for healthcare applications: a data-driven approach, PhD thesis, School of Information Technology, Deakin Univeristy.

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Title Building stable predictive models for healthcare applications: a data-driven approach
Author Kamkar, Iman
Institution Deakin Univeristy
School School of Information Technology
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name PhD
Thesis advisor Gupta, Sunil KumarORCID iD for Gupta, Sunil Kumar orcid.org/0000-0002-3308-1930
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Date submitted 2016-07
Keyword(s) biomedical informatics
electronic medical records
information technology
clinical predictive models
Summary Analysing health related data enable us to transform data into predictive models. These models can be used to accurately make diagnosis or prognosis about states of a patient, which cannot be investigated directly. The scope of this thesis lies within the realm of biomedical informatics, an interdisciplinary field at the crossroads of medicine and computer science.
Language eng
Field of Research 010404 Probability Theory
010405 Statistical Theory
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
Description of original xxviii, 216 pages : illustrations, tables, graphs, some coloured
Copyright notice ┬ęThe author. All Rights Reserved.
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093414

Document type: Thesis
Collections: Higher degree theses (full text)
Open Access Collection
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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.