Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/32311
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | BECKER, Thijs | |
dc.contributor.advisor | PEETERS, Liesbet | |
dc.contributor.author | Kasunumba, Noah | |
dc.date.accessioned | 2020-10-01T11:33:33Z | - |
dc.date.available | 2020-10-01T11:33:33Z | - |
dc.date.issued | 2020 | |
dc.identifier.uri | http://hdl.handle.net/1942/32311 | - |
dc.format.mimetype | Application/pdf | |
dc.language | en | |
dc.publisher | tUL | |
dc.title | Towards personalized medicine: Predicting disability progression of MS patients from evoked potentials | |
dc.type | Theses and Dissertations | |
local.bibliographicCitation.jcat | T2 | |
dc.description.notes | Master of Statistics-Bioinformatics | |
local.type.specified | Master thesis | |
item.fullcitation | Kasunumba, Noah (2020) Towards personalized medicine: Predicting disability progression of MS patients from evoked potentials. | - |
item.accessRights | Open Access | - |
item.fulltext | With Fulltext | - |
item.contributor | Kasunumba, Noah | - |
Appears in Collections: | Master theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
894a5f92-0a21-41fe-b122-f4e36149e835.pdf | 1.29 MB | Adobe PDF | View/Open |
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