Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/33283
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dc.contributor.advisorBecker, Thijs-
dc.contributor.advisorLiesenborgs, Jori-
dc.contributor.advisorCleuren, Bart-
dc.contributor.authorYPERMAN, Jan-
dc.date.accessioned2021-02-03T11:49:29Z-
dc.date.available2021-02-03T11:49:29Z-
dc.date.issued2021-
dc.date.submitted2021-01-22T12:20:48Z-
dc.identifier.urihttp://hdl.handle.net/1942/33283-
dc.language.isoen-
dc.titleBridging the gap between machine learning and evoked potentials in MS-
dc.typeTheses and Dissertations-
local.format.pages190-
local.bibliographicCitation.jcatT1-
local.type.refereedRefereed-
local.type.specifiedPhd thesis-
local.type.programmeVSC-
local.provider.typePdf-
local.uhasselt.uhpubyes-
local.uhasselt.internationalno-
item.contributorYPERMAN, Jan-
item.accessRightsEmbargoed Access-
item.fulltextWith Fulltext-
item.fullcitationYPERMAN, Jan (2021) Bridging the gap between machine learning and evoked potentials in MS.-
item.embargoEndDate2026-01-19-
Appears in Collections:Research publications
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