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dc.contributor.authorRomagnoni, Albertoen
dc.contributor.authorJégou, Simonen
dc.contributor.authorVan Steen, Kristelen
dc.contributor.authorWainrib, Gillesen
dc.contributor.authorHugot, Jean-Pierreen
dc.contributor.authorInternational Inflammatory Bowel Disease Genetics Consortium (IIBDGC),en
dc.date.accessioned2019-10-30T00:31:03Z
dc.date.available2019-10-30T00:31:03Z
dc.date.issued2019-07-17en
dc.identifier.issn2045-2322
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/298214
dc.format.mediumElectronicen
dc.languageengen
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectInternational Inflammatory Bowel Disease Genetics Consortium (IIBDGC)en
dc.subjectHumansen
dc.subjectCrohn Diseaseen
dc.subjectGenetic Predisposition to Diseaseen
dc.subjectArea Under Curveen
dc.subjectLogistic Modelsen
dc.subjectROC Curveen
dc.subjectGenotypeen
dc.subjectPolymorphism, Single Nucleotideen
dc.subjectAllelesen
dc.subjectDecision Treesen
dc.subjectNonlinear Dynamicsen
dc.subjectModels, Geneticen
dc.subjectFemaleen
dc.subjectMaleen
dc.subjectINDEL Mutationen
dc.subjectGenome-Wide Association Studyen
dc.subjectGenotyping Techniquesen
dc.subjectDeep Learningen
dc.subjectNeural Networks, Computeren
dc.titleComparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.en
dc.typeArticle
prism.issueIdentifier1en
prism.publicationDate2019en
prism.publicationNameScientific reportsen
prism.startingPage10351
prism.volume9en
dc.identifier.doi10.17863/CAM.45266
dcterms.dateAccepted2019-07-03en
rioxxterms.versionofrecord10.1038/s41598-019-46649-zen
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-07-17en
dc.contributor.orcidHugot, Jean-Pierre [0000-0002-8446-6056]
dc.identifier.eissn2045-2322
rioxxterms.typeJournal Article/Reviewen


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International