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Combining Multiple Connectomes Improves Predictive Modeling of Phenotypic Measures
Resting-state and task-based functional connectivity matrices, or connectomes, are powerful predictors of individual differences in phenotypic measures. However, most of the current state-of-the-art algorithms only build predictive models based on a single connectome for each individual. This approa...
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| Udgivet i: | Neuroimage |
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| Main Authors: | , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2019
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6765422/ https://ncbi.nlm.nih.gov/pubmed/31336188 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2019.116038 |
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