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 Author Myles, P
Showing results 1 to 7 of 7
| Issue Date | Title | Author(s) |
| 1-Sep-2021 | Bayesboost: Identifying and Handling Bias Using Synthetic Data Generators | Draghi, B; Wang, Z; Myles, P; Tucker, A |
| 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 |
| 10-Jan-2024 | Identifying and handling data bias within primary healthcaredata using synthetic data generators | Draghi, B; Wang, Z; Myles, P; Tucker, A |
| 2024 | Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations | Alattal, D; Azar, AK; Myles, P; Branson, R; Abdulhussein, H; Tucker, A |
| 24-Jan-2023 | The potential synergies between synthetic data and in silico trials in relation to generating representative virtual population cohorts | Myles, P; Ordish, J; Tucker, A |
| 2-Feb-2021 | Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks | de Benedetti, J; Oues, N; Wang, Z; Myles, P; Tucker, A |
