Regulators’ Pioneer Fund
Funder: Innovate UKDuration: October 2018 - March 2020
Developing and applying datasets for the validation of algorithms, including machine learning / artificially intelligent algorithms in medical devices.
People
Name | Telephone | Office | ||
---|---|---|---|---|
Professor Allan Tucker Professor
T: +44 (0)1895 266933
E: allan.tucker@brunel.ac.uk |
+44 (0)1895 266933 | allan.tucker@brunel.ac.uk | Wilfred Brown Building 218 |
Outputs
Wang, Z., Myles, P., Jain, A., Keidel, JL., Liddi, R., Mackillop, L., 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 (online). 7 - 9 June. IEEE. pp. 259 - 264. ISSN: 2372-918X Open Access Link
de Benedetti, J., Oues, N., Wang, Z., Myles, P. and Tucker, A. (2021) 'Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks'.Joint European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD: ECML PKDD 2020 Workshops. Ghent, Belgium [virtual]. 2 - 18 September. Springer International Publishing. pp. 38 - 47. ISSN: 1865-0929 Open Access Link
Wang, Z., Myles, P. and Tucker, A. (2021) 'Generating and evaluating cross-sectional synthetic electronic healthcare data: Preserving data utility and patient privacy'. Computational Intelligence, in press (2). pp. 1 - 33. ISSN: 0824-7935 Open Access Link
Tucker, A., Wang, Z., Rotalinti, Y. and Myles, P. (2020) 'Generating High-Fidelity Synthetic Patient Data for Assessing Machine Learning Healthcare Software'. npj digital medicine, 3 (1). pp. 1 - 13. ISSN: 2398-6352 Open Access Link
Wang, Z., Myles, P. and Tucker, A. (2019) 'Generating and evaluating synthetic UK primary care data: Preserving data utility & patient privacy'.2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS). IEEE. pp. 126 - 131. ISSN: 1063-7125