Task-driven ICA feature generation for accurate and interpretable prediction using fMRI.
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 pro...
| Main Authors: | , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2012
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