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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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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
Journal:
NeuroImage More from this journal
Volume:
60
Issue:
1
Pages:
189-203
Publication date:
2012-03-01
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
Language:
English
Keywords:
Pubs id:
pubs:228654
UUID:
uuid:fa6c3bc1-4f32-4554-a2f2-f7c2105259c9
Local pid:
pubs:228654
Source identifiers:
228654
Deposit date:
2012-12-19

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