Fetching the paper…
Reading the bibliography…
Counterfactual prediction is a fundamental task in decision-making.
A graphical approach to the identification and estimation of causal parameters in mortality studies with sustained exposure periods
James Robins · 1987
Earlier work this paper cites.
Correcting for non-compliance in randomized trials using structural nested mean models
James Robins · 1994
Earlier work this paper cites.
Marginal structural models and causal inference in epidemiology
James Robins, Miguel Hernan, and Babette Brumback · 2000
Earlier work this paper cites.
History-adjusted marginal structural models and statically-optimal dynamic treatment regimens
Mark van der Laan, Maya Petersen, and Marshall Joffe · 2005
Earlier work this paper cites.
Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes
Liliana Orellana, James Robins, and Andrea Rotnitzky · 2008
Earlier work this paper cites.
Estimation of the causal effects of time varying exposures
James Robins and Miguel Hernan · 2009
Earlier work this paper cites.
Intervening on risk factors for coronary heart disease: An application of the parametric g-formula
Sarah Taubman, James Robins, Murray Mittleman, and Miguel Hernan · 2009
Earlier work this paper cites.
Variational learning of inducing variables in sparse gaussian processes
Michalis Titsias · 2009
Cited alongside, same era.
Comparative effectiveness of dynamic treatment regimes: An application of the parametric g-formula
Jessica Young, Lauren Cain, James Robins, Eilis O’Reilly, and Miguel Hernan · 2011
Cited alongside, same era.
Structural nested models and g-estimation: The partially realized promise
Stijn Vansteelandt and Marshall Joffe · 2014
Cited alongside, same era.
Retain: An interpretable predictive model for healthcare using reverse time attention mechanism
Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, and Walter Stewart · 2016
Cited alongside, same era.
A theoretically grounded application of dropout in recurrent neural networks
Yarin Gal and Zoubin Ghahramani · 2016
Cited alongside, same era.
Deep counterfactual networks with propensity-dropout
Surviving sepsis campaign: International guidelines for management of sepsis and septic shock: 2016
Andrew Rhodes, Waleed Evans, Laura E.and Alhazzani, Mitchell M. Levy, Massimo Antonelli, Ricard Ferrer, Anand Kumar, Jonathan E. Sevransky, Charles L. Sprung, Mark E. Nunnally, et al · 2017
Later among the works it cites.
Intravenous fluid therapy in critically ill adults
Simon Finfer, John Myburgh, and Rinaldo Bellomo · 2018
Later among the works it cites.
Deep-treat: Learning optimal personalized treatments from observational data using neural networks
Onur Atan, James Jordan, and Mihaela van der Schaar · 2018
Later among the works it cites.
Ganite: Estimation of individualized treatment effects using generative adversarial nets
Jinsung Yoon, James Jordan, and Mihaela van der Schaar · 2018
Later among the works it cites.
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
Cao Xiao, Edward Choi, and Jimeng Sun · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M Ahmed Alaa, Michael Weisz, and Mihaela van der Schaar · 2017
Cited alongside, same era.
Reliable decision support using counterfactual models
Peter Schulam and Suchi Saria · 2017
Cited alongside, same era.
Causal Inference
Miguel Hernan and James Robins
Cited in the paper.
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
James Robins
Cited in the paper.
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
James Robins
Cited in the paper.
Cvsim: an open-source cardiovascular simulator for teaching and research
Thomas Heldt, Ramakrishna Mukkamala, George B Moody, and Roger G Mark
Cited in the paper.
CVSim: An open-source cardiovascular simulator for teaching and research
T Heldt, R Mukkamala, GB Moody, and RG Mark
Cited in the paper.
Forecasting treatment responses over time using recurrent marginal structural networks
Bryan Lim, Ahmed Alaa, and Mihaela van der Schaar · 2018
Later among the works it cites.
A clinically applicable approach to continuous prediction of future acute kidney injury
Nenad Tomašev, Xavier Glorot, Jack W Rae, Michal Zielinski, Harry Askham, Andre Saraiva, Anne Mottram, Clemens Meyer, Suman Ravuri, Ivan Protsyuk, et al · 2019
Later among the works it cites.