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dc.contributor.authorDuncan, Dominique
dc.contributor.authorVespa, Paul
dc.contributor.authorPitkanen, Asla
dc.contributor.authorBraimah, Adebayo
dc.contributor.authorLapinlampi, Niina
dc.contributor.authorToga, Arthur W
dc.date.accessioned2019-03-28T08:52:41Z
dc.date.available2019-03-28T08:52:41Z
dc.date.issued2019
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/7505
dc.description.abstractWe describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time.
dc.language.isoenglanti
dc.publisherElsevier BV
dc.relation.ispartofseriesNeurobiology of Disease
dc.relation.urihttp://dx.doi.org/10.1016/j.nbd.2018.05.026
dc.rightsCC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectbiomarkers
dc.subjectEEG
dc.subjectepilepsy
dc.subjectepileptogenesis
dc.subjectinformatics
dc.subjectMRI
dc.subjectneuroimaging
dc.titleBig data sharing and analysis to advance research in post-traumatic epilepsy
dc.description.versionfinal draft
dc.contributor.departmentA.I. Virtanen -instituutti
uef.solecris.id54978168en
dc.type.publicationTieteelliset aikakauslehtiartikkelit
dc.rights.accessrights© Elsevier Inc
dc.relation.doi10.1016/j.nbd.2018.05.026
dc.description.reviewstatuspeerReviewed
dc.format.pagerange127-136
dc.relation.issn0969-9961
dc.relation.volume123
dc.rights.accesslevelopenAccess
dc.type.okmA2
uef.solecris.openaccessEi


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