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Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data
Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (...
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| Publicat a: | IEEE/ACM Trans Comput Biol Bioinform |
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| Autors principals: | , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5885321/ https://ncbi.nlm.nih.gov/pubmed/29610102 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TCBB.2015.2440244 |
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