Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject synthetic data
Showing results 1 to 5 of 5
| Issue Date | Title | Author(s) |
|---|---|---|
| 7-Jun-2021 | Evaluating a longitudinal synthetic data generator using real world data | Wang, Z; Myles, P; Jain, A; Keidel, JL; Liddi, R; Mackillop, L; Velardo, C; Tucker, A |
| 9-Nov-2020 | Generating High-Fidelity Synthetic Patient Data for Assessing Machine Learning Healthcare Software | Tucker, A; Wang, Z; Rotalinti, Y; Myles, P |
| 2-Feb-2021 | Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks | de Benedetti, J; Oues, N; Wang, Z; Myles, P; Tucker, A |
| 5-Aug-2026 | Synthetic data to boost under-represented patients and create virtual trial cohorts: the RATE-AF case study | Draghi, Barbara; Attal, Dima; Kotecha, Dipak; Myles, Puja; Chapman, Matthew; Champsi, Asgher; Branson, Richard; Bunting, Karina V; Mobley, Alastair R; Tucker, Allan |
| 30-Aug-2023 | Synthetic Electricity Consumption Data Generation Using Tabular Generative Adversarial Networks | Tun, TP; Pisica, I |