Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26033
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dc.contributor.authorWang, Z-
dc.contributor.authorMyles, P-
dc.contributor.authorJain, A-
dc.contributor.authorKeidel, JL-
dc.contributor.authorLiddi, R-
dc.contributor.authorMackillop, L-
dc.contributor.authorVelardo, C-
dc.contributor.authorTucker, A-
dc.coverage.spatialAveiro, Portugal (online)-
dc.date.accessioned2023-03-02T14:18:37Z-
dc.date.available2023-03-02T14:18:37Z-
dc.date.issued2021-06-07-
dc.identifier.citationWang, Z. et al. (2021) 'Evaluating a longitudinal synthetic data generator using real world data', 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 7-9 June, pp. 259-264. doi: 10.1109/CBMS52027.2021.00074.en_US
dc.identifier.isbn978-1-6654-4121-6 (ebk)-
dc.identifier.isbn978-1-6654-3107-1 (PoD)-
dc.identifier.issn2372-918X-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/26033-
dc.description.sponsorshipThe work presented in this paper was funded by NHSX using the synthetic data generation and evaluation framework developed under a grant awarded to the Medicines and Healthcare products Regulatory Agency (MHRA) by The Department for Business, Energy and Industrial Strategy (BEIS) and managed by Innovate UK.en_US
dc.format.extent259 - 264-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsCopyright © 2021 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. See https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ for more information-
dc.rights.urihttps://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.source2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)-
dc.source2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)-
dc.subjectsynthetic dataen_US
dc.subjectBayesian networksen_US
dc.subjectmachine learningen_US
dc.subjectdiabetesen_US
dc.titleEvaluating a longitudinal synthetic data generator using real world dataen_US
dc.typeConference Paperen_US
dc.identifier.doihttps://doi.org/10.1109/CBMS52027.2021.00074-
dc.relation.isPartOfProceedings - IEEE Symposium on Computer-Based Medical Systems-
pubs.finish-date2021-06-09-
pubs.finish-date2021-06-09-
pubs.publication-statusPublished-
pubs.start-date2021-06-07-
pubs.start-date2021-06-07-
pubs.volume2021-June-
dc.identifier.eissn2372-9198-
dc.rights.holderInstitute of Electrical and Electronics Engineers (IEEE)-
Appears in Collections:Dept of Computer Science Research Papers

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