Puja Myles

According to our database, Puja Myles authored at least 17 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Probabilistic Versus Deep Generative Models: A Fairness Centred Evaluation of Synthetic Healthcare Tabular Data.

Dima R. Alattal, Barbara Draghi, Puja Myles, Richard Branson, Allan Tucker

Int. J. Comput. Intell. Syst., December, 2026

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, May, 2025

A consensus privacy metrics framework for synthetic data.

Lisa Pilgram, Fida Kamal Dankar, Jörg Drechsler, Mark Elliot, Josep Domingo-Ferrer, Paul Francis, Murat Kantarcioglu, Linglong Kong, Bradley A. Malin, Krishnamurty Muralidhar, Puja Myles, Fabian Prasser, Jean Louis Raisaro, Chao Yan, Khaled El Emam

Patterns, 2025

Crossing borders securely: synthetic data and federated networks for privacy-preserving access to real-world data and emerging use cases.

Echo H. Wang, Puja Myles, Randi Foraker, Sengwee Toh, Lucy Mosquera, Khaled El Emam, Mehmet Burcu

npj Digit. Medicine, 2025

2024

Bias-Aware Synthetic Data Generation: A Tailored Use Case-Driven Approach.

Barbara Draghi, Puja Myles, Allan Tucker

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2024

Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels.

Ylenia Rotalinti, Puja Myles, Allan Tucker

Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

2023

Privacy Assessment of Synthetic Patient Data.

Ferdoos Hossein Nezhad, Ylenia Rotalinti, Puja Myles, Allan Tucker

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 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

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

The Impact of Bias on Drift Detection in AI Health Software.

Asal Khoshravan Azar, Barbara Draghi, Ylenia Rotalinti, Puja Myles, Allan Tucker

Proceedings of the Artificial Intelligence in Medicine, 2023

2022

Detecting Drift in Healthcare AI Models Based on Data Availability.

Ylenia Rotalinti, Allan Tucker, Michael Lonergan, Puja Myles, Richard Branson

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

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

BayesBoost: Identifying and Handling Bias Using Synthetic Data Generators.

Barbara Draghi, Zhenchen Wang, Puja Myles, Allan Tucker

Proceedings of the Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2021

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

Proceedings of the 34th IEEE International Symposium on Computer-Based Medical Systems, 2021

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

Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks.

Juan de Benedetti, Namir Oues, Zhenchen Wang, Puja Myles, Allan Tucker

Proceedings of the ECML PKDD 2020 Workshops, 2020

2019

Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy.

Zhenchen Wang, Puja Myles, Allan Tucker

Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems, 2019

2018

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, Richard Branson, Karel G. M. Moons, Gary S. Collins, John P. A. Ioannidis, Chris C. Holmes, Harry Hemingway

CoRR, 2018