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Canonical feature selection for joint regression and multi-class identification in Alzheimer’s disease diagnosis
Fusing information from different imaging modalities is crucial for more accurate identification of the brain state because imaging data of different modalities can provide complementary perspectives on the complex nature of brain disorders. However, most existing fusion methods often extract featur...
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| I publikationen: | Brain Imaging Behav |
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| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2016
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4747862/ https://ncbi.nlm.nih.gov/pubmed/26254746 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11682-015-9430-4 |
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