| 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 | 272 | 2019 |
| 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 | 232 | 2017 |
| Limits of estimating heterogeneous treatment effects: Guidelines for practical algorithm design A Alaa, M Schaar International Conference on Machine Learning (ICML), 129-138, 2018 | 109 | 2018 |
| How artificial intelligence and machine learning can help healthcare systems respond to COVID-19 M Van der Schaar, AM Alaa, A Floto, A Gimson, S Scholtes, A Wood, ... Machine Learning 110, 1-14, 2021 | 97 | 2021 |
| 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 | 96 | 2020 |
| 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 | 93 | 2017 |
| 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 | 87 | 2020 |
| 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 | 86 | 2018 |
| Deep Counterfactual Networks with Propensity-Dropout AM Alaa, M Weisz, M van der Schaar ICML 2017 - Workshop on Principled Approaches to Deep Learning, 2017 | 79 | 2017 |
| Attentive state-space modeling of disease progression AM Alaa, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 11334-11344, 2019 | 69 | 2019 |
| 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 | 69 | 2018 |
| Lifelong Bayesian Optimization Y Zhang, J Jordon, AM Alaa, M van der Schaar arXiv preprint arXiv:1905.12280, 2019 | 65* | 2019 |
| Demystifying Black-box Models with Symbolic Metamodels AM Alaa, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 11301-11311, 2019 | 61 | 2019 |
| 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 | 61 | 2016 |
| Validating Causal Inference Models via Influence Functions A Alaa, M Van Der Schaar International Conference on Machine Learning (ICML), 191-201, 2019 | 60 | 2019 |
| 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 | 52 | 2020 |
| 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 | 49 | 2018 |
| 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 | 49 | 2017 |
| 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 | 48 | 2016 |
| 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 | 47 | 2020 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing InstituteVerified email at ee.ucla.edu
