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Predictive modelling using neuroimaging data in the presence of confounds
When training predictive models from neuroimaging data, we typically have available non-imaging variables such as age and gender that affect the imaging data but which we may be uninterested in from a clinical perspective. Such variables are commonly referred to as ‘confounds’. In this work, we firs...
में बचाया:
| में प्रकाशित: | Neuroimage |
|---|---|
| मुख्य लेखकों: | , , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
Academic Press
2017
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5391990/ https://ncbi.nlm.nih.gov/pubmed/28143776 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2017.01.066 |
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