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Fused Lasso Regression for Identifying Differential Correlations in Brain Connectome Graphs.
Yu, Donghyeon; Lee, Sang Han; Lim, Johan; Xiao, Guanghua; Craddock, R Cameron; Biswal, Bharat B.
Afiliación
  • Yu D; Department of Statistics, Inha University, Incheon, South Korea.
  • Lee SH; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
  • Lim J; Department of Statistics, Seoul National University, Seoul, South Korea.
  • Xiao G; University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
  • Craddock RC; Department of Diagnostic Medicine, Dell Medical School, The University of Texas at Ausstin, TX 78712, USA.
  • Biswal BB; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Stat Anal Data Min ; 11(5): 203-226, 2018 Oct.
Article en En | MEDLINE | ID: mdl-34386148
In this paper, we propose a procedure to find differential edges between two graphs from high-dimensional data. We estimate two matrices of partial correlations and their differences by solving a penalized regression problem. We assume sparsity only on differences between two graphs, not graphs themselves. Thus, we impose an ℓ 2 penalty on partial correlations and an ℓ 1 penalty on their differences in the penalized regression problem. We apply the proposed procedure to finding differential functional connectivity between healthy individuals and Alzheimer's disease patients.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Stat Anal Data Min Año: 2018 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Stat Anal Data Min Año: 2018 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Estados Unidos