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A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis

 
dc.contributor.authorD'hondt, Robbe
dc.contributor.authorMoylett, Sinead
dc.contributor.authorGoris, An
dc.contributor.authorVens, Celine
dc.contributor.imecauthorD'hondt, Robbe
dc.contributor.imecauthorVens, Celine
dc.contributor.orcidimecD'hondt, Robbe::0000-0001-7843-2178
dc.contributor.orcidimecVens, Celine::0000-0003-0983-256X
dc.date.accessioned2024-09-30T08:48:21Z
dc.date.available2024-09-25T17:29:16Z
dc.date.available2024-09-30T08:48:21Z
dc.date.issued2023
dc.description.wosFundingTextThis work was funded by Research Fund Flanders (FWO fellowship 1S38023N) and supported by the Flemish government (through the AI Research Program) and Stichting MS Research (through a Monique Blom-de Wagt grant). We furthermore thank Professor Benedicte Dubois, neurologist at UZ Leuven, for collecting the data that was used retrospectively in this work.
dc.identifier.doi10.1007/978-3-031-34344-5_3
dc.identifier.eisbn978-3-031-34344-5
dc.identifier.isbn978-3-031-34343-8
dc.identifier.issn2945-9133
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44567
dc.publisherSPRINGER INTERNATIONAL PUBLISHING AG
dc.source.beginpage25
dc.source.conference21st International Conference on Artificial Intelligence in Medicine (AIME)
dc.source.conferencedateJUN 12-15, 2023
dc.source.conferencelocationPortoroz
dc.source.endpage34
dc.source.journalLecture Notes in Artificial Intelligence
dc.source.numberofpages10
dc.source.volume13897
dc.title

A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis

dc.typeProceedings paper
dspace.entity.typePublication
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