Reinforcement Learning for Finding Optimal Dynamic Treatment Regimes Using Observational Data

This Guide to Statistics and Methods provides an overview of using observational data and reinforcement learning strategies to develop dynamic treatment regimes for patients who are critically ill.

Corresponding Author: Andrea Rotnitzky, PhD, Hans Rosling Center for Population Health, University of Washington, 3980 15th Ave NE, Box 351617, Seattle, WA 98195-1617 (arotnitz@uw.edu).

Link to the article in your story

We encourage you to link out to this article in your story using the link below. It includes an access token that will give free access to the article for your readers up to one year after publication. (The link will be live after the article publishes and embargo is lifted.)

Please see the article for additional information, including full author list, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

Need more information? Contact us.