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Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. NEW METHOD: This study introduces folded concave penalized (FCP) sparse logistic regression to ident...
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| Publicado no: | J Neurosci Methods |
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| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4913043/ https://ncbi.nlm.nih.gov/pubmed/27102045 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jneumeth.2016.04.016 |
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