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RLoptimal - Optimal Adaptive Allocation Using Deep Reinforcement Learning
An implementation to compute an optimal adaptive allocation rule using deep reinforcement learning in a dose-response study (Matsuura et al. (2022) <doi:10.1002/sim.9247>). The adaptive allocation rule can directly optimize a performance metric, such as power, accuracy of the estimated target dose, or mean absolute error over the estimated dose-response curve.
Last updated 1 months ago
5.95 score 4 stars 21 scripts 278 downloads![](https://github.com/matsuurakentaro/rlescalation/raw/HEAD/man/figures/logo.png)
RLescalation - Optimal Dose Escalation Using Deep Reinforcement Learning
An implementation to compute an optimal dose escalation rule using deep reinforcement learning in phase I oncology trials (Matsuura et al. (2023) <doi:10.1080/10543406.2023.2170402>). The dose escalation rule can directly optimize the percentages of correct selection (PCS) of the maximum tolerated dose (MTD).
Last updated 7 days ago
4.18 score 182 downloads