Bilal A. Mateen

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 11

Top Topics

Nearest Neighbour

Majority Voting

Machine Learning

Feature Importance

Top Venues

BMC Medical Informatics Decis. Mak.

Nat. Mach. Intell.

Publications

Ashwini Venkatasubramaniam, Bilal A. Mateen, Beverley M. Shields, Andrew T. Hattersley, Angus G. Jones, Sebastian J. Vollmer, John M. Dennis
Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine. BMC Medical Informatics Decis. Mak. 23 (1) (2023)
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 O'Reilly, Sebastian Vollmerteke
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. CoRR (2022)
Rebecca Knowles, Bilal A. Mateen, Yo Yehudi
We need to talk about the lack of investment in digital research infrastructure. Nat. Comput. Sci. 1 (3) (2021)
James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer
Model updating after interventions paradoxically introduces bias. AISTATS (2021)
Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer
Improving the quality of machine learning in health applications and clinical research. Nat. Mach. Intell. 2 (10) (2020)
Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A. Mateen, Sebastian J. Vollmer
Debiasing classifiers: is reality at variance with expectation? CoRR (2020)
James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer
Model updating after interventions paradoxically introduces bias. CoRR (2020)
Frithjof Gressmann, Franz J. Király, Bilal A. Mateen, Harald Oberhauser
Probabilistic supervised learning. CoRR (2018)
Franz J. Király, Bilal A. Mateen, Raphael Sonabend
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature. CoRR (2018)
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 (2018)
Bilal A. Mateen, Matthias Bussas, Catherine Doogan, Denise Waller, Alessia Saverino, Franz J. Király, E. Diane Playford
Machine Learning in Falls Prediction; A cognition-based predictor of falls for the acute neurological in-patient population. CoRR (2016)