Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity
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- 作者：Barnaly Rashida ; b ; Mohammad R. Arbabshirania ; g ; Eswar Damarajua ; b ; Mustafa S. Cetina ; f ; Robyn Millerb ; Godfrey D. Pearlsonc ; d ; e ; Vince D. Calhouna ; b ; d ; f ; vcalhoun@mrn.org" class="auth_mail" title="E-mail the corresponding author
- 关键词：fMRI ; Resting-state ; Dynamic functional network connectivity ; Classification ; Schizophrenia ; Bipolar
- 刊名：NeuroImage
- 出版年：2016
- 出版时间：1 July 2016
- 年：2016
- 卷：134
- 期：Complete
- 页码：645-657
- 全文大小：2589 K
文摘
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Performed classification using static and dynamic connectivity features in schizophrenia and bipolar disorder during rest.
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Classification using connectivity features discriminates subjects into appropriate diagnostic groups with high accuracy.
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Classification using dynamic connectivity features has significantly higher predictive accuracy than static FNC.
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Combining both connectivity features does not add significant information for classification purposes.