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Puja Myles
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2020 – today
- 2024
- [c9]Ylenia Rotalinti, Puja Myles, Allan Tucker:
Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels. IDA (1) 2024: 167-178 - 2023
- [c8]Asal Khoshravan Azar, Barbara Draghi, Ylenia Rotalinti, Puja Myles, Allan Tucker
:
The Impact of Bias on Drift Detection in AI Health Software. AIME 2023: 313-322 - [c7]Ferdoos Hossein Nezhad, Ylenia Rotalinti, Puja Myles, Allan Tucker:
Privacy Assessment of Synthetic Patient Data. CBMS 2023: 1-6 - [c6]Dima R. Alattal, Zhenchen Wang
, Puja Myles, Allan Tucker:
Creating Synthetic Geospatial Patient Data to Mimic Real Data Whilst Preserving Privacy: *2022 35th International Symposium on Computer-Based Medical Systems (CBMS). CBMS 2023: 7-12 - 2022
- [c5]Ylenia Rotalinti, Allan Tucker
, Michael Lonergan, Puja Myles, Richard Branson:
Detecting Drift in Healthcare AI Models Based on Data Availability. PKDD/ECML Workshops (2) 2022: 243-258 - 2021
- [j2]Zhenchen Wang
, Puja Myles, Allan Tucker:
Generating and evaluating cross-sectional synthetic electronic healthcare data: Preserving data utility and patient privacy. Comput. Intell. 37(2): 819-851 (2021) - [c4]Zhenchen Wang
, Puja Myles, Anu Jain, James L. Keidel, Roberto Liddi, Lucy Mackillop, Carmelo Velardo, Allan Tucker:
Evaluating a Longitudinal Synthetic Data Generator using Real World Data. CBMS 2021: 259-264 - [c3]Barbara Draghi, Zhenchen Wang, Puja Myles, Allan Tucker:
BayesBoost: Identifying and Handling Bias Using Synthetic Data Generators. LIDTA@ECML/PKDD 2021: 49-62 - 2020
- [j1]Allan Tucker
, Zhenchen Wang
, Ylenia Rotalinti, Puja Myles
:
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software. npj Digit. Medicine 3 (2020) - [c2]Juan de Benedetti, Namir Oues, Zhenchen Wang
, Puja Myles, Allan Tucker:
Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks. PKDD/ECML Workshops 2020: 38-47
2010 – 2019
- 2019
- [c1]Zhenchen Wang
, Puja Myles, Allan Tucker:
Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy. CBMS 2019: 126-131 - 2018
- [i1]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:
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness. CoRR abs/1812.10404 (2018)
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