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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 (...

詳細記述

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書誌詳細
出版年:IEEE/ACM Trans Comput Biol Bioinform
主要な著者: Zhao, Yize, Kang, Jian, Long, Qi
フォーマット: Artigo
言語:Inglês
出版事項: 2018
主題:
オンライン・アクセス: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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