Subclass-based multi-task learning for Alzheimer's disease diagnosis.

In this work, we propose a novel subclass-based multi-task learning method for feature selection in computer-aided Alzheimer's Disease (AD) or Mild Cognitive Impairment (MCI) diagnosis. Unlike the previous methods that often assumed a unimodal data distribution, we take into account the underlying m...

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Detalles Bibliográficos
Publicado en:Frontiers in Aging Neuroscience Vol. 6; pp. 1 - 13
Autores principales: Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
Formato: Journal Article
Publicado: Frontiers Media S.A. Aug2014
Acceso en línea:Ver este registro en EBSCOhost