Can machine learning improve the diagnostic prediction of imaging measures in dementia and epilepsy?
- Research Opportunity
- PhD, Masters by Research, Master of Biomedical Science
- Medicine and Radiology
- Royal Melbourne Hospital
|Dr Vijay Venkatramanemail@example.com||0383440401||Personal web page|
|Prof. Roland Bammerfirstname.lastname@example.org||Personal web page|
Quantitative imaging measures have shown to be clinically useful to render a diagnosis. We believe that a variant of the machine learning approach called deep learning can be used to better identify and delineate the regions of interest at much improved speed and accuracy.
In this project, we will develop novel neuroimaging tools driven by machine learning to precisely identify and measure pathologies in epilepsy and dementia. We are looking for two students (one PhD position and one Master of Science position) to work on projects related: (i) implementation of machine learning approaches in image analysis or (ii) clinical evaluation in big data clinical trials in dementia, stroke, and epilepsy.
The students will be mentored and work within a multidisciplinary team in the Royal Melbourne Hospital, Florey Institute of Neuroscience and Mental Health, and University of Melbourne as well as other collaborators (in Melbourne and internationally). Publication of results is expected at the end of the project.
Additional top-up PhD scholarship will be available for qualified students. The specific details of the project will be discussed with interested candidates.
Faculty Research Themes
School Research Themes
PhD, Masters by Research, Master of Biomedical Science
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research
For further information about this research, please contact a supervisor.
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Research NodeRoyal Melbourne Hospital
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