Ahmed M. Alaa

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Mihaela van der SchaarUniversity of Cambridge, The Alan Turing InstituteVerified email at ee.ucla.edu
Jinsung YoonResearch Scientist at Google Cloud AIVerified email at google.com
Ioana BicaResearch Scientist at DeepMindVerified email at google.com
Anthony PhilippakisVerified email at google.com
David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Atul J. ButteDirector, Bakar Computational Health Sciences Institute, University of California, San FranciscoVerified email at ucsf.edu
Adrian L HarrisProfessor of Medical Oncology, Oxford UniversityVerified email at oncology.ox.ac.uk
Deepti GurdasaniKirby Institute, University of New South WalesVerified email at unsw.edu.au
Mark van der LaanJiann-Ping Hsu/Karl E. Peace Professor of Biostatistics & Statistics, University of California BerkeleyVerified email at berkeley.edu
Alicia CurthMicrosoft Research CambridgeVerified email at microsoft.com
Irene Y. ChenAssistant Professor, UC Berkeley and UC San FranciscoVerified email at berkeley.edu
Lars van der LaanPh.D. Student in Statistics, University of Washington, SeattleVerified email at uw.edu
Marie-Laure CharpignonPhD Candidate in Social & Engineering Systems and Statistics, MITVerified email at mit.edu
David OuyangCardiology, Cedars Sinai Medical CenterVerified email at cshs.org
Pradeep NatarajanMassachusetts General Hospital, Harvard Medical School, Broad Institute of Harvard and MITVerified email at partners.org
Maya Petersen, MD, PhDProfessor of Biostatistics, Epidemiology, and Computational Precision Health UC BerkeleyVerified email at berkeley.edu
Emre KıcımanSenior Principal Research Manager, Microsoft ResearchVerified email at microsoft.com
Pengtao XieAssistant Professor, UC San Diego; Adjunct Faculty, MBZUAIVerified email at eng.ucsd.edu
James ZouStanford UniversityVerified email at stanford.edu
Travis Ian ZackOncology Fellow, University of California, San FranciscoVerified email at ucsf.edu

Ahmed M. Alaa

Other namesAhmed Alaa

Assistant Professor, UC Berkeley and UCSF

Verified email at berkeley.edu - Homepage

Machine Learning Statistics Healthcare Causal Inference Biomedical Data Science


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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	511	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	363	2017
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	211	2020
How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models AM Alaa, B van Breugel, E Saveliev, M van der Schaar International Conference on Machine Learning (ICML), 2022	202	2022
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	202	2021
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	187	2020
Limits of estimating heterogeneous treatment effects: Guidelines for practical algorithm design A Alaa, M Schaar International Conference on Machine Learning (ICML), 129-138, 2018	163	2018
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	162	2018
Attentive state-space modeling of disease progression AM Alaa, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 11334-11344, 2019	131	2019
Conformal Time-series Forecasting K Stankevičiūtė, A Alaa, M van der Schaar Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), 2021	130*	2021
Lifelong Bayesian Optimization Y Zhang, J Jordon, AM Alaa, M van der Schaar arXiv preprint arXiv:1905.12280, 2019	123*	2019
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	122	2017
Demystifying Black-box Models with Symbolic Metamodels AM Alaa, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 11301-11311, 2019	114	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	114	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	114	2017
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	112	2020
Validating Causal Inference Models via Influence Functions A Alaa, M Van Der Schaar International Conference on Machine Learning (ICML), 191-201, 2019	108	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	87	2016
Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results … C Lee, A Light, A Alaa, D Thurtle, M van der Schaar, VJ Gnanapragasam The Lancet Digital Health 3 (3), e158-e165, 2021	84	2021
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	74	2018

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