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Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data
[chapter]
2016
Lecture Notes in Computer Science
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view corresponding to a specific modality or a combination of several modalities. However, existing methods usually ignore the underlying coherence among views, which may lead to suboptimal learning performance. In this paper, we propose a viewaligned hypergraph
doi:10.1007/978-3-319-46720-7_36
pmid:28066842
pmcid:PMC5207479
fatcat:nlhwmg7d2jhsplmexhwhvoyidm