%0 Journal Article %T Predicting conversion to clinically definite multiple sclerosis using machine learning on the basis of cerebral grey matter segmentations %+ University Hospital Basel [Basel] %+ Vrije Universiteit Amsterdam [Amsterdam] (VU) %+ Service de Neurologie [Rennes] = Neurology [Rennes] %+ Centre d'Investigation Clinique [Rennes] (CIC) %A Bendfeldt, K. %A Taschler, B. %A Gaetano, L. %A Madoerin, P. %A Kuster, P. %A Mueller-Lenke, N. %A Amann, M. %A Vrenken, H. %A Barkhof, F. %A Borgwardt, S. %A Kloeppel, S. %A Nichols, T. E. %A Suarez, G. %A Kappos, Ludwig %A Edan, Gilles %A Freedman, M. S. %A Montalban, X. %A Hartung, H. -P. %A Pohl, C. %A Sandbrink, R. %A Wuerfel, J. %A Radue, E. -W. %A Sprenger, T %< avec comité de lecture %@ 1352-4585 %J Multiple Sclerosis Journal %I SAGE Publications %S 31st Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Barcelona, SPAIN, OCT 07-10, 2015 %V 21 %N 11 %P 498--499 %8 2015-09 %D 2015 %Z Life Sciences [q-bio]Journal articles %X no abstract %G English %L hal-01259385 %U https://univ-rennes.hal.science/hal-01259385 %~ UNIV-RENNES1 %~ HL %~ CIC %~ CIC203 %~ STATS-UR1 %~ UR1-UFR-SVE %~ UR1-HAL %~ UR1-SDV %~ TEST-UNIV-RENNES %~ TEST-UR-CSS %~ UNIV-RENNES %~ UR1-BIO-SA