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MULTI-SOURCE FEATURE LEARNING FOR JOINT ANALYSIS OF INCOMPLETE MULTIPLE HETEROGENEOUS NEUROIMAGING DATA
Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of...
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| Autores principales: | , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2012
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3358419/ https://ncbi.nlm.nih.gov/pubmed/22498655 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2012.03.059 |
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