Bilal A. Mateen

According to our database, Bilal A. Mateen authored at least 12 papers between 2016 and 2024.

Collaborative distances:

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

2024

Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

2023

Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine.

Ashwini Venkatasubramaniam, Bilal A. Mateen, Beverley M. Shields, Andrew T. Hattersley, Angus G. Jones, Sebastian J. Vollmer, John M. Dennis

BMC Medical Informatics Decis. Mak., December, 2023

2022

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data.

Oscar Giles, Kasra Hosseini, Grigorios Mingas, Oliver Strickson, Louise Bowler, Camila Rangel Smith, Harrison Wilde, Jen Ning Lim, Bilal A. Mateen, Kasun Amarasinghe, Rayid Ghani, Alison J. Heppenstall, Nik Lomax, Nick Malleson, Martin T. O'Reilly, Sebastian J. Vollmer

CoRR, 2022

2021

We need to talk about the lack of investment in digital research infrastructure.

Rebecca Knowles, Bilal A. Mateen, Yo Yehudi

Nat. Comput. Sci., 2021

Model updating after interventions paradoxically introduces bias.

James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Improving the quality of machine learning in health applications and clinical research.

Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer

Nat. Mach. Intell., 2020

Debiasing classifiers: is reality at variance with expectation?

Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A. Mateen, Sebastian J. Vollmer

CoRR, 2020

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

NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature.

Franz J. Király, Bilal A. Mateen, Raphael Sonabend

CoRR, 2018

Probabilistic supervised learning.

Frithjof Gressmann, Franz J. Király, Bilal A. Mateen, Harald Oberhauser

CoRR, 2018

2016

Machine Learning in Falls Prediction; A cognition-based predictor of falls for the acute neurological in-patient population.

Bilal A. Mateen, Matthias Bussas, Catherine Doogan, Denise Waller, Alessia Saverino, Franz J. Király, E. Diane Playford

CoRR, 2016