Package: RLescalation 1.0.2

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).

Authors:Kentaro Matsuura [aut, cre, cph]

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RLescalation.pdf |RLescalation.html✨
RLescalation/json (API)
NEWS

# Install 'RLescalation' in R:
install.packages('RLescalation', repos = c('https://matsuurakentaro.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/matsuurakentaro/rlescalation/issues

On CRAN:

Conda:

4.18 score 221 downloads 8 exports 15 dependencies

Last updated 1 months agofrom:43b611861e. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-winOKMar 13 2025
R-4.5-macOKMar 13 2025
R-4.5-linuxOKMar 13 2025
R-4.4-winOKMar 13 2025
R-4.4-macOKMar 13 2025
R-4.4-linuxOKMar 13 2025
R-4.3-winOKMar 13 2025
R-4.3-macOKMar 13 2025

Exports:clean_python_settingscompute_rl_scenariosEscalationRulelearn_escalation_rulerl_config_setrl_dnn_configsetup_pythonsimulate_one_trial

Dependencies:glueherejsonlitelatticeMatrixnleqslvpngR6rappdirsRcppRcppTOMLreticulaterlangrprojrootwithr

Optimal Dose Escalation Using Deep Reinforcement Learning

Kentaro Matsuura

Rendered fromRLescalation.Rmdusingknitr::rmarkdownon Mar 13 2025.

Last update: 2025-02-10
Started: 2024-12-31