An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data.
The need for algorithms that capture subject-specific abnormalities (SSA) in neuroimaging data is increasingly recognized across many neuropsychiatric disorders. However, the effects of initial distributional properties (e.g., normal versus non-normally distributed data), sample size, and typical pr...
| Publicado en: | Brain Imaging & Behavior Vol. 12; no. 2; pp. 437 - 449 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Apr2018
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| Acceso en línea: | Ver este registro en EBSCOhost |