A machine learning approach to assess injury risk in elite youth football players

dc.contributor.author	Rommers, N.
dc.contributor.author	Rössler, R.
dc.contributor.author	Verhaegen, E.
dc.contributor.author	Vandecasteele, Florian
dc.contributor.author	Verstockt, Steven
dc.contributor.author	Vaeyens, R.
dc.contributor.author	Lenoir, M.
dc.contributor.author	D'Hondt, E.
dc.contributor.author	Witvrouw, E.
dc.contributor.imecauthor	Verstockt, Steven
dc.contributor.orcidimec	Verstockt, Steven::0000-0003-1094-2184
dc.date.accessioned	2021-10-29T03:13:51Z
dc.date.available	2021-10-29T03:13:51Z
dc.date.embargo	9999-12-31
dc.date.issued	2020
dc.identifier.doi	10.1249/MSS.0000000000002305
dc.identifier.issn	0195-9131
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/35852
dc.source.beginpage	1745
dc.source.endpage	1751
dc.source.issue	8
dc.source.journal	Medicine & Science in Sports & Exercise
dc.source.volume	52
dc.title	A machine learning approach to assess injury risk in elite youth football players
dc.type	Journal article
dspace.entity.type	Publication
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