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DC Field | Value | Language |
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dc.contributor.author | Wang, Z | - |
dc.contributor.author | Myles, P | - |
dc.contributor.author | Jain, A | - |
dc.contributor.author | Keidel, JL | - |
dc.contributor.author | Liddi, R | - |
dc.contributor.author | Mackillop, L | - |
dc.contributor.author | Velardo, C | - |
dc.contributor.author | Tucker, A | - |
dc.coverage.spatial | Aveiro, Portugal (online) | - |
dc.date.accessioned | 2023-03-02T14:18:37Z | - |
dc.date.available | 2023-03-02T14:18:37Z | - |
dc.date.issued | 2021-06-07 | - |
dc.identifier.citation | Wang, 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.isbn | 978-1-6654-4121-6 (ebk) | - |
dc.identifier.isbn | 978-1-6654-3107-1 (PoD) | - |
dc.identifier.issn | 2372-918X | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/26033 | - |
dc.description.sponsorship | The 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.extent | 259 - 264 | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | Copyright © 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.uri | https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ | - |
dc.source | 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) | - |
dc.source | 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) | - |
dc.subject | synthetic data | en_US |
dc.subject | Bayesian networks | en_US |
dc.subject | machine learning | en_US |
dc.subject | diabetes | en_US |
dc.title | Evaluating a longitudinal synthetic data generator using real world data | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | https://doi.org/10.1109/CBMS52027.2021.00074 | - |
dc.relation.isPartOf | Proceedings - IEEE Symposium on Computer-Based Medical Systems | - |
pubs.finish-date | 2021-06-09 | - |
pubs.finish-date | 2021-06-09 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2021-06-07 | - |
pubs.start-date | 2021-06-07 | - |
pubs.volume | 2021-June | - |
dc.identifier.eissn | 2372-9198 | - |
dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © 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 | 1.37 MB | Adobe PDF | View/Open |
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