Predicting conversion to clinically definite multiple sclerosis using machine learning on the basis of cerebral grey matter segmentations

K. Bendfeldt; B. Taschler; L. Gaetano; P. Madoerin; P. Kuster; N. Mueller-Lenke; M. Amann; H. Vrenken; F. Barkhof; S. Borgwardt; S. Kloeppel; T. E. Nichols; G. Suarez; Ludwig Kappos; Gilles Edan; M. S. Freedman; X. Montalban; H. -P. Hartung; C. Pohl; R. Sandbrink; J. Wuerfel; E. -W. Radue; T Sprenger

Journal articles

Predicting conversion to clinically definite multiple sclerosis using machine learning on the basis of cerebral grey matter segmentations

K. Bendfeldt ¹ B. Taschler L. Gaetano ¹ P. Madoerin ¹ P. Kuster ¹ N. Mueller-Lenke ¹ M. Amann ¹ H. Vrenken F. Barkhof ² S. Borgwardt ¹ S. Kloeppel T. E. Nichols G. Suarez Ludwig Kappos ¹ Gilles Edan ^{3, 4} M. S. Freedman X. Montalban H. -P. Hartung C. Pohl R. Sandbrink J. Wuerfel ¹ E. -W. Radue ¹ T Sprenger ¹

1 University Hospital Basel [Basel]

2 VU - Vrije Universiteit Amsterdam [Amsterdam]

3 Service de Neurologie [Rennes] = Neurology [Rennes]

4 CIC - Centre d'Investigation Clinique [Rennes]

Abstract : no abstract

Document type :

Journal articles

Domain :

Life Sciences [q-bio]

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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01259385
Contributor : Laurent Jonchère Connect in order to contact the contributor
Submitted on : Wednesday, January 20, 2016 - 1:09:55 PM
Last modification on : Wednesday, March 30, 2022 - 2:37:03 PM

Predicting conversion to clinically definite multiple sclerosis using machine learning on the basis of cerebral grey matter segmentations

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Predicting conversion to clinically definite multiple sclerosis using machine learning on the basis of cerebral grey matter segmentations

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