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Journal article

Task-driven ICA feature generation for accurate and interpretable prediction using fMRI.

Abstract:

Functional Magnetic Resonance Imaging (fMRI) shows significant potential as a tool for predicting clinically important information such as future disease progression or drug effect from brain activity. Multivariate techniques have been developed that combine fMRI signals from across the brain to produce more robust predictive capabilities than can be obtained from single regions. However, the high dimensionality of fMRI data makes overfitting a significant problem. Reliable methods are needed...

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Publication status:
Published

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Authors


Trachtenberg, AJ More by this author
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Institution:
University of Oxford
Department:
Oxford, MSD, Psychiatry
Howard, MA More by this author
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Journal:
NeuroImage
Volume:
60
Issue:
1
Pages:
189-203
Publication date:
2012-03-05
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
URN:
uuid:fa6c3bc1-4f32-4554-a2f2-f7c2105259c9
Source identifiers:
228654
Local pid:
pubs:228654

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