Ioana Bica
Ioana Bica
PhD Student, University of Oxford, The Alan Turing Institute
Verified email at eng.ox.ac.uk
Title
Cited by
Cited by
Year
Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study
P Baqui*, I Bica*, V Marra, A Ercole, M van Der Schaar
The Lancet Global Health 8 (8), e1018-e1026, 2020
2122020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
I Bica, AM Alaa, J Jordon, M van der Schaar
International Conference on Learning Representations (ICLR), 2020
362020
From real‐world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges
I Bica, AM Alaa, C Lambert, M van der Schaar
Clinical Pharmacology & Therapeutics 109 (1), 87-100, 2021
292021
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders
I Bica, AM Alaa, M van der Schaar
International Conference on Machine Learning (ICML), 2020
172020
Machine learning for clinical trials in the era of COVID-19
WR Zame, I Bica, C Shen, A Curth, HS Lee, S Bailey, J Weatherall, ...
Statistics in Biopharmaceutical Research 12 (4), 506-517, 2020
142020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
I Bica*, J Jordon*, M van der Schaar
Neural Information Processing Systems (NeurIPS), 2020
102020
Multi-omics data integration using cross-modal neural networks
I Bica, P Velickovic, H Xiao, P Lio
ESANN, 2018
82018
Strictly Batch Imitation Learning by Energy-based Distribution Matching
D Jarrett*, I Bica*, M van der Schaar
Neural Information Processing Systems (NeurIPS), 2020
52020
Unsupervised generative and graph representation learning for modelling cell differentiation
I Bica*, H Andrs-Terr*, A Cvejic, P Li
Nature Scientific Reports, 2019
52019
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All
SK Sarkar, S Roy, E Alsentzer, MBA McDermott, F Falck, I Bica, G Adams, ...
Machine Learning for Health, 1-11, 2020
22020
Learning "What-if" Explanations for Sequential Decision-Making
I Bica, D Jarrett, A Hyk, M van der Schaar
International Conference on Learning Representations (ICLR), 2021
1*2021
Clairvoyance: A Pipeline Toolkit for Medical Time Series
D Jarrett*, J Yoon*, I Bica, Z Qian, A Ercole, M van der Schaar
International Conference on Learning Representations (ICLR), 2021
12021
OrganITE: Optimal transplant donor organ offering using an individual treatment effect
J Berrevoets, J Jordon, I Bica, A Gimson, M van der Schaar
Neural Information Processing Systems (NeurIPS), 2020
12020
The Medkit-Learn (ing) Environment: Medical Decision Modelling through Simulation
AJ Chan, I Bica, A Huyuk, D Jarrett, M van der Schaar
arXiv preprint arXiv:2106.04240, 2021
2021
Model-Attentive Ensemble Learning for Sequence Modeling
VD Bourgin, I Bica, M van der Schaar
Machine Learning for Health (ML4H) Workshop (NeurIPS), 2021
2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge
T Kyono*, I Bica*, Z Qian, M van der Schaar
arXiv preprint arXiv:2102.06271, 2021
2021
Learning Matching Representations for Individualized Organ Transplantation Allocation
C Xu, AM Alaa, I Bica, BD Ershoff, M Cannesson, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
2021
Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors
P Baqui, V Marra, AM Alaa, I Bica, A Ercole, M van der Schaar
medarxiv, 2021
2021
CellVGAE: An unsupervised scRNA-seq analysis workflow with graph attention networks
D Buterez, I Bica, I Tariq, H Andrs-Terr, P Li
bioRxiv, 2020
2020
Individualised Dose-Response Estimation using Generative Adversarial Nets
I Bica, J Jordon, M van der Schaar
2019
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Articles 1–20