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Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists
- Source :
- NeuroImage: a journal of brain function 216, 116745 (2020). doi:10.1016/j.neuroimage.2020.116745, NeuroImage, NeuroImage, 2020, NeuroImage, Elsevier, 2020, NeuroImage, Vol 216, Iss, Pp 116745-(2020)
- Publication Year :
- 2020
- Publisher :
- Academic Press, 2020.
-
Abstract
- NeuroImage: a journal of brain function 216, 116745 (2020). doi:10.1016/j.neuroimage.2020.116745<br />Published by Academic Press, Orlando, Fla
- Subjects :
- Big Data
Computer science
Modality fusion
Cognitive Neuroscience
Neuroimaging
050105 experimental psychology
lcsh:RC321-571
Machine Learning
03 medical and health sciences
0302 clinical medicine
Humans
0501 psychology and cognitive sciences
[MATH]Mathematics [math]
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Systems neuroscience
Models, Statistical
05 social sciences
Data Science
Neurosciences
Deep phenotyping
Data science
Variable (computer science)
ComputingMethodologies_PATTERNRECOGNITION
Neurology
Haystack
Canonical correlation
030217 neurology & neurosurgery
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 10538119 and 10959572
- Database :
- OpenAIRE
- Journal :
- NeuroImage: a journal of brain function 216, 116745 (2020). doi:10.1016/j.neuroimage.2020.116745, NeuroImage, NeuroImage, 2020, NeuroImage, Elsevier, 2020, NeuroImage, Vol 216, Iss, Pp 116745-(2020)
- Accession number :
- edsair.doi.dedup.....fa693cd4fc04bf1aad7c2d0846de09be
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2020.116745