Package: RLescalation 1.0.1

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'))

Peer review:

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

On CRAN:

4.00 score 18 downloads 8 exports 15 dependencies

Last updated 11 hours agofrom:59a05711f5. Checks:7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 12 2025
R-4.5-winOKJan 12 2025
R-4.5-linuxOKJan 12 2025
R-4.4-winOKJan 12 2025
R-4.4-macOKJan 12 2025
R-4.3-winOKJan 12 2025
R-4.3-macOKJan 12 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 Jan 12 2025.

Last update: 2025-01-09
Started: 2024-12-31