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High Classification Accuracy for Schizophrenia with Rest and Task fMRI Data
We present a novel method to extract classification features from functional magnetic resonance imaging (fMRI) data collected at rest or during the performance of a task. By combining a two-level feature identification scheme with kernel principal component analysis (KPCA) and Fisher’s linear discri...
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| 主要な著者: | , , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Research Foundation
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3366580/ https://ncbi.nlm.nih.gov/pubmed/22675292 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2012.00145 |
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