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dc.contributor.authorParamasivam, Vijayajothi
dc.contributor.supervisorAssoc. Prof. Amandeep Sidhuen_US
dc.date.accessioned2017-07-20T06:16:04Z
dc.date.available2017-07-20T06:16:04Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/20.500.11937/54143
dc.description.abstract

This thesis proposes a novel hybrid methodology that couples computational fluid dynamic (CFD) and data mining (DM) techniques that is applied to a multi-dimensional medical dataset in order to study potential disease development statistically. This approach allows an alternate solution for the present tedious and rigorous CFD methodology being currently adopted to study the influence of geometric parameters on hemodynamics in the human abdominal aortic aneurysm. This approach is seen as a “marriage” between medicine and computer domains.

en_US
dc.publisherCurtin Universityen_US
dc.titleConceptual framework of a novel hybrid methodology between computational fluid dynamics and data mining techniques for medical dataset applicationen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSarawak, Malaysiaen_US
curtin.accessStatusOpen accessen_US
curtin.facultySarawak, Malaysiaen_US


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