MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry

Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern classification using SVMs facilitates predicting conver...

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Detaylı Bibliyografya
Asıl Yazarlar:	Bendfeldt, K, Taschler, B, Gaetano, L, Madoerin, P, Kuster, P, Mueller-Lenke, N, Amann, M, Vrenken, H, Wottschel, V, Barkhof, F, Borgwardt, S, Klöppel, S, Wicklein, EM, Kappos, L, Edan, G, Freedman, MS, Montalbán, X, Hartung, HP, Pohl, C, Sandbrink, R, Sprenger, T, Radue, EW, Wuerfel, J, Nichols, TE
Materyal Türü:	Journal article
Baskı/Yayın Bilgisi:	Springer US 2018

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry

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