Ahmed M. Alaa
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Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
AM Alaa, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 3424-3432, 2017
1272017
Cardiovascular disease risk prediction using automated machine learning: a prospective study of 423,604 UK Biobank participants
AM Alaa, T Bolton, E Di Angelantonio, JHF Rudd, M van der Schaar
PloS one 14 (5), e0213653, 2019
1152019
Deep multi-task gaussian processes for survival analysis with competing risks
AM Alaa, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 2326-2334, 2017
612017
Limits of estimating heterogeneous treatment effects: Guidelines for practical algorithm design
A Alaa, M Schaar
International Conference on Machine Learning (ICML), 129-138, 2018
512018
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes
AM Alaa, J Yoon, S Hu, M van der Schaar
IEEE Transactions on Biomedical Engineering, 2016
432016
ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission
J Yoon, AM Alaa, S Hu, M van der Schaar
International Conference on Machine Learning (ICML), 1680-1689, 2016
412016
Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks
B Lim, A Alaa, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 7493-7503, 2018
402018
Deep Counterfactual Networks with Propensity-Dropout
AM Alaa, M Weisz, M van der Schaar
ICML 2017 - Workshop on Principled Approaches to Deep Learning, 2017
402017
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
AM Alaa, M van der Schaar
International Conference on Machine Learning (ICML), 2018
382018
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
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
AM Alaa, S Hu, M van der Schaar
International Conference on Machine Learning (ICML), 60-69, 2017
362017
Attentive state-space modeling of disease progression
AM Alaa, M van der Schaar
Advances in Neural Information Processing Systems (NeurIPS), 11334-11344, 2019
352019
ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening
AM Alaa, KH Moon, W Hsu, M van der Schaar
IEEE Transactions on Multimedia, 2016
332016
Between-centre differences for COVID-19 ICU mortality from early data in England
Z Qian, AM Alaa, M van Der Schaar, A Ercole
Intensive Care Medicine (ICM), 2020
292020
Validating Causal Inference Models via Influence Functions
A Alaa, M Van Der Schaar
International Conference on Machine Learning (ICML), 191-201, 2019
292019
Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation
J Yoon, WR Zame, A Banerjee, M Cadeiras, AM Alaa, M van der Schaar
PloS one 13 (3), e0194985, 2018
292018
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 and Therapeutics, 2020
282020
Bayesian nonparametric causal inference: Information rates and learning algorithms
AM Alaa, M van der Schaar
IEEE Journal of Selected Topics in Signal Processing, 2017
262017
Prognostication and risk factors for cystic fibrosis via automated machine learning
AM Alaa, M van der Schaar
Nature Scientific reports 8 (1), 1-19, 2018
252018
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference
AM Alaa, M van der Schaar
Journal of Machine Learning Research, 2016
242016
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Artikelen 1–20