Karla Diaz-Ordaz

According to our database, Karla Diaz-Ordaz authored at least 8 papers between 2019 and 2025.

Collaborative distances:

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

2025

DECOVID: A UK Two-Center Harmonized Database of Acute Care Electronic Health Records for COVID-19 Research.

Louis J. M. Aslett, Andreea Avramescu, Nicholas Bakewell, Isabel Birds, Louise Bowler, Michael P. J. Camilleri, Sheng-Chia Chung, David A. Clifton, Samuel N. Cohen, Nathan Constantine-Cooke, Eric G. Daub, Shaun M. Davidson, Spiros C. Denaxas, Karla Diaz-Ordaz, Richard Feltbower, Suzy Gallier, Stephen Gardiner, Francesca Gasperoni, Robert J. B. Goudie, Rebecca E. Green, Marlous S. Hall, Chris Holmes, John R. Hurst, Mark M. Iles, João Jorge, Emma Karoune, Ruth H. Keogh, Ruairidh King, Ruth King, Paul D. W. Kirk, Roman Klapaukh, Samaneh Kouchaki, Alvina Grace Lai, Nathan Lea, Clemence Leyrat, Kezhi Li, Watjana Lilaonitkul, Huiqi Y. Lu, Terry Lyons, Ann-Marie Mallon, Andrew A. Manderson, Nicolò Margaritella, Joshua Matteson, Sam Morley, Hannah Nicholls, Martin T. O'Reilly, Christina Pagel, Edward Palmer, Jack Roberts, Timothy J. Roberts, David S. Robertson, James Robinson, Patrick Rockenschaub, Roy A. Ruddle, Elizabeth Sapey, Luis Santos, Andrew A. S. Soltan, Fang Gao-Smith, Colin Starr, Oliver Strickson, Li Su, Mia S. Tackney, Johan Hilge Thygesen, Ana Torralbo, Alice M. Turner, Catalina A. Vallejos, Chenyang Wang, Kirstie J. Whitaker, Tony Whitehouse, David R. Westhead, Wai Keong Wong, Yue Wu, Lingyi Yang, Xiaoxu Zou

Data, 2025

Investigating fair data acquisition for risk prediction in resource-constrained settings.

Ioanna Thoma, Elisabeth Abhayaratna, Matthew Sperrin, Karla Diaz-Ordaz, Ricardo Silva, Brieuc Lehmann

Proceedings of the European Workshop on Algorithmic Fairness, 2025

2024

Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data.

Matthew Pryce, Karla Diaz-Ordaz, Ruth H. Keogh, Stijn Vansteelandt

CoRR, 2024

Explainable AI for survival analysis: a median-SHAP approach.

Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes

CoRR, 2024

2023

PWSHAP: A Path-Wise Explanation Model for Targeted Variables.

Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes

Proceedings of the International Conference on Machine Learning, 2023

2021

Informative presence and observation in routine health data: A review of methodology for clinical risk prediction.

Rose Sisk, Lijing Lin, Matthew Sperrin, Jessica K. Barrett, Brian D. M. Tom, Karla Diaz-Ordaz, Niels Peek, Glen P. Martin

J. Am. Medical Informatics Assoc., 2021

On Locality of Local Explanation Models.

Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Machine learning in policy evaluation: new tools for causal inference.

Noemi Kreif, Karla DiazOrdaz

CoRR, 2019