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Generation of realistic synthetic validation healthcare datasets using generative adversarial networks

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Bilici Ozyigit, Eda, Arvanitis, Theodoros N. and Despotou, George (2020) Generation of realistic synthetic validation healthcare datasets using generative adversarial networks. In: The Importance of Health Informatics in Public Health during a Pandemic. Studies in Health Technology and Informatics, 272 . I O S Press, pp. 322-325. ISBN 9781643680927

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Official URL: http://dx.doi.org/10.3233/SHTI200560

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Abstract

Background:
Assurance of digital health interventions involves, amongst others, clinical validation, which requires large datasets to test the application in realistic clinical scenarios. Development of such datasets is time consuming and challenging in terms of maintaining patient anonymity and consent.
Objective:
The development of synthetic datasets that maintain the statistical properties of the real datasets.
Method:
An artificial neural network based, generative adversarial network was implemented and trained, using numerical and categorical variables, including ICD-9 codes from the MIMIC III dataset, to produce a synthetic dataset.
Results:
The synthetic dataset, exhibits a correlation matrix highly similar to the real dataset, good Jaccard similarity and passing the KS test.
Conclusions:
The proof of concept was successful with the approach being promising for further work.

Item Type: Book Item
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
R Medicine > R Medicine (General)
Divisions: Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Medical care -- Technological innovations, Medical informatics, Wireless communication systems in medical care , Machine learning , Data sets, Data protection
Series Name: Studies in Health Technology and Informatics
Publisher: I O S Press
ISBN: 9781643680927
ISSN: 0926-9630
Book Title: The Importance of Health Informatics in Public Health during a Pandemic
Official Date: 2020
Dates:
DateEvent
2020Published
19 May 2020Accepted
Volume: 272
Page Range: pp. 322-325
DOI: 10.3233/SHTI200560
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 6 July 2020
Date of first compliant Open Access: 6 July 2020
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDInnovate UKhttp://dx.doi.org/10.13039/501100006041

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