Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26033
Title: Evaluating a longitudinal synthetic data generator using real world data
Authors: Wang, Z
Myles, P
Jain, A
Keidel, JL
Liddi, R
Mackillop, L
Velardo, C
Tucker, A
Keywords: synthetic data;Bayesian networks;machine learning;diabetes
Issue Date: 7-Jun-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
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.
URI: http://bura.brunel.ac.uk/handle/2438/26033
DOI: http://dx.doi.org/10.1109/CBMS52027.2021.00074
ISBN: 978-1-6654-4121-6 (ebk)
978-1-6654-3107-1 (PoD)
ISSN: 2372-918X
Appears in Collections:Publications

Files in This Item:
File Description SizeFormat 
FullText.pdf1.37 MBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.