Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness. - Sebastian J. Vollmer; Bilal A. Mateen; Gergo Bohner; Franz J. Király; Rayid Ghani; Pall Jonsson; Sarah Cumbers; Adrian Jonas; Katherine S. L. McAllister; Puja Myles; David Granger; Mark Birse; et al. (CoRR, 2018)

Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy. - Zhenchen Wang; Puja Myles; Allan Tucker (CBMS, 2019)

Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks. - Juan de Benedetti; Namir Oues; Zhenchen Wang; Puja Myles; Allan Tucker (PKDD/ECML Workshops, 2020)

Generating high-fidelity synthetic patient data for assessing machine learning healthcare software. - Allan Tucker; Zhenchen Wang; Ylenia Rotalinti; Puja Myles (npj Digit. Medicine, 2020)

Evaluating a Longitudinal Synthetic Data Generator using Real World Data. - Zhenchen Wang; Puja Myles; Anu Jain; James L. Keidel; Roberto Liddi; Lucy Mackillop; Carmelo Velardo; Allan Tucker (CBMS, 2021)

BayesBoost: Identifying and Handling Bias Using Synthetic Data Generators. - Barbara Draghi; Zhenchen Wang; Puja Myles; Allan Tucker (LIDTA@ECML/PKDD, 2021)

Generating and evaluating cross-sectional synthetic electronic healthcare data: Preserving data utility and patient privacy. - Zhenchen Wang; Puja Myles; Allan Tucker (Comput. Intell., 2021)

Detecting Drift in Healthcare AI Models Based on Data Availability. - Ylenia Rotalinti; Allan Tucker; Michael Lonergan; Puja Myles; Richard Branson (PKDD/ECML Workshops (2), 2022)

The Impact of Bias on Drift Detection in AI Health Software. - Asal Khoshravan Azar; Barbara Draghi; Ylenia Rotalinti; Puja Myles; Allan Tucker (AIME, 2023)

Creating Synthetic Geospatial Patient Data to Mimic Real Data Whilst Preserving Privacy: *2022 35th International Symposium on Computer-Based Medical Systems (CBMS). - Dima R. Alattal; Zhenchen Wang; Puja Myles; Allan Tucker (CBMS, 2023)

Privacy Assessment of Synthetic Patient Data. - Ferdoos Hossein Nezhad; Ylenia Rotalinti; Puja Myles; Allan Tucker (CBMS, 2023)

Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels. - Ylenia Rotalinti; Puja Myles; Allan Tucker (IDA (1), 2024)

A Consensus Privacy Metrics Framework for Synthetic Data. - Lisa Pilgram; Fida K. Dankar; Jörg Drechsler; Mark Elliot; Josep Domingo-Ferrer; Paul Francis; Murat Kantarcioglu; Linglong Kong; Bradley A. Malin; Krishnamurty Muralidhar; Puja Myles; Fabian Prasser; et al. (CoRR, 2025)

Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations. - Dima R. Alattal; Asal Khoshravan Azar; Puja Myles; Richard Branson; Hatim Abdulhussein; Allan Tucker (CoRR, 2025)