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dc.contributor.authorBrian Caffo*
dc.contributor.authorJian Kang*
dc.contributor.authorHan Liu*
dc.date.accessioned2021-02-12T00:58:07Z
dc.date.available2021-02-12T00:58:07Z
dc.date.issued2017*
dc.date.submitted2017-07-06 13:27:36*
dc.identifier22979*
dc.identifier.issn16648714*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/57714
dc.description.abstractBig data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.*
dc.languageEnglish*
dc.relation.ispartofseriesFrontiers Research Topics*
dc.subjectRC321-571*
dc.subjectQ1-390*
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciencesen_US
dc.subject.otherfMRI*
dc.subject.otherNeuroscience*
dc.subject.otherfunctional connectivity*
dc.subject.otherEEG*
dc.subject.otherClassification*
dc.subject.otherprediction*
dc.subject.otherbig data*
dc.subject.otherMEG*
dc.titleRecent Advances and Challenges on Big Data Analysis in Neuroimaging*
dc.typebook
oapen.identifier.doi10.3389/978-2-88945-128-9*
oapen.relation.isPublishedBybf5ce210-e72e-4860-ba9b-c305640ff3ae*
oapen.relation.isbn9782889451289*
oapen.pages195*


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