Stochastic Tree Search for Estimating Optimal Dynamic Treatment Regimes

Yilun Sun & Lu Wang
A dynamic treatment regime (DTR) is a sequence of decision rules that adapt to the time-varying states of an individual. Black-box learning methods have shown great potential in predicting the optimal treatments; however, the resulting DTRs lack interpretability, which is of paramount importance for medical experts to understand and implement. We present a stochastic tree-based reinforcement learning (ST-RL) method for estimating optimal DTRs in a multistage multitreatment setting with data from either randomized trials or...
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