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dc.contributor.authorCasamitjana Díaz, Adrià
dc.contributor.authorVilaplana Besler, Verónica
dc.contributor.authorPuch Giner, Santi
dc.contributor.authorAduriz Saiz, Asier
dc.contributor.authorOperto, Grégory
dc.contributor.authorCacciaglia, Raffaele
dc.contributor.authorFalcón, Carlos
dc.contributor.authorMolinuevo, José Luis
dc.contributor.authorGispert, Juan Domingo
dc.contributor.authorLópez Molina, Carlos Alejandro
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2020-07-06T09:41:56Z
dc.date.available2020-07-06T09:41:56Z
dc.date.issued2020-03-25
dc.identifier.citationCasamitjana, A. [et al.]. NeAT: a nonlinear analysis toolbox for neuroimaging. "Neuroinformatics", 25 Març 2020, p. 1-14.
dc.identifier.issn1539-2791
dc.identifier.urihttp://hdl.handle.net/2117/192478
dc.description.abstractNeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. NeAT provides a wide range of statistical and machine learning non-linear methods for model estimation, several metrics based on curve fitting and complexity for model inference and a graphical user interface (GUI) for visualization of results. We illustrate its usefulness on two study cases where non-linear effects have been previously established. Firstly, we study the nonlinear effects of Alzheimer’s disease on brain morphology (volume and cortical thickness). Secondly, we analyze the effect of the apolipoprotein APOE-e4 genotype on brain aging and its interaction with age. NeAT is fully documented and publicly distributed at https://imatge-upc.github.io/neat-tool/.
dc.description.sponsorshipThis work has been partially supported by the project MALEGRA TEC2016-75976-R financed by the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund (ERDF). Adrià Casamitjana is supported by the Spanish “Ministerio de Educación, Cultura y Deporte” FPU Research Fellowship. Juan D. Gispert holds a “‘Ramón y Cajal’” fellowship (RYC-2013-13054). Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wpcontent/uploads/how to apply/ADNI Acknowledgement List.pdf.
dc.format.extent14 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
dc.subject.lcshMachine learning
dc.subject.lcshNeurology
dc.subject.otherNonlinear
dc.subject.otherNeuroimaging
dc.subject.otherGLM
dc.subject.otherGAM
dc.subject.otherSVR
dc.subject.otherAlzheimer's disease
dc.subject.otherInference
dc.subject.otherAPOE
dc.titleNeAT: a nonlinear analysis toolbox for neuroimaging
dc.typeArticle
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacNeurologia
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.identifier.doi10.1007/s12021-020-09456-w
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://link.springer.com/article/10.1007/s12021-020-09456-w
dc.rights.accessOpen Access
local.identifier.drac28651082
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TEC2016-75976-R
local.citation.authorCasamitjana, A.; Vilaplana, V.; Puch, S.; Aduriz, A.; Lopez, C.; Operto, G.; Cacciaglia, R.; Falcón, C.; Molinuevo, J.; Gispert, J. D.
local.citation.publicationNameNeuroinformatics
local.citation.startingPage1
local.citation.endingPage14


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