| Literature DB >> 28003710 |
Jingxiang Chen1, Yufeng Liu2, Donglin Zeng1, Rui Song3, Yingqi Zhao4, Michael R Kosorok5.
Abstract
Xu, Müller, Wahed, and Thall proposed a Bayesian model to analyze an acute leukemia study involving multi-stage chemotherapy regimes. We discuss two alternative methods, Q-learning and O-learning, to solve the same problem from the machine learning point of view. The numerical studies show that these methods can be flexible and have advantages in some situations to handle treatment heterogeneity while being robust to model misspecification.Entities:
Keywords: Dynamic treatment regimes; Multi-stage chemotherapy regimes; O-learning; Q-learning
Year: 2016 PMID: 28003710 PMCID: PMC5167482 DOI: 10.1080/01621459.2016.1200914
Source DB: PubMed Journal: J Am Stat Assoc ISSN: 0162-1459 Impact factor: 5.033