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Using machine learning for detecting anomalous accesses to EHRs: a comparative analysis and case study

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorLu, X.
dc.contributor.authorBelleman, B.
dc.date.accessioned2020-11-23T19:00:31Z
dc.date.available2020-11-23T19:00:31Z
dc.date.issued2020
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/38181
dc.description.sponsorshipUtrecht University
dc.format.extent2900539
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleUsing machine learning for detecting anomalous accesses to EHRs: a comparative analysis and case study
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuArtificial Intelligence


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