Puja Myles

Orcid: 0000-0002-8976-890X

According to our database1, Puja Myles authored at least 12 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

2023
Privacy Assessment of Synthetic Patient Data.
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).
Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

The Impact of Bias on Drift Detection in AI Health Software.
Proceedings of the Artificial Intelligence in Medicine, 2023

2022
Detecting Drift in Healthcare AI Models Based on Data Availability.
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.
Comput. Intell., 2021

BayesBoost: Identifying and Handling Bias Using Synthetic Data Generators.
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.
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.
npj Digit. Medicine, 2020

Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks.
Proceedings of the ECML PKDD 2020 Workshops, 2020

2019
Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy.
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.
CoRR, 2018


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