Dynamic Treatment Regimes
By Anastasios A. Tsiatis, Marie Davidian, Shannon T. Holloway, Eric B. Laber. 2019
73 citations recorded by the source corpus.
Subfields: Statistics and Probability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Stefan Wager
- Xinkun Nie
- Emma Brunskill
- Zhuoran Yang
- Yuchen Xie
- Zhaoran Wang
- Susan Athey
- Edward H. Kennedy
Citations in the corpus
- Learning When-to-Treat Policies (2019, methodology): “…on dynamic decision rules is beyond the scope of this article; instead, we refer the reader to recent review papers (Vansteelandt and Joffe 2014; Kosorok and Laber 2019; Clifton and Laber 2020; Levine et al. 2020), as well as textbooks by Chakraborty and Moodie (2013) and Tsiatis et al. (2019).”
- A Theoretical Analysis of Deep Q-Learning (2019, methodology): “2019); Fujimoto et al. (2019). Moreover, Q-learning, and reinforcement learning methods in general, have been widely applied to dynamic treatment regimes (DTR) (Chakraborty, 2013; Laber et al., 2014; Tsiatis, 2019), where the goal is to find sequential decision rules for individual patients that adap”