Learning Dynamic Treatment Regime (DTR) via meta-learners
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Apr 28, 2023 - R
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dynamic-treatment-regimens
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This repository contains code to estimate sample size needed to compare dynamic treatment regimens using longitudinal count outcomes from a Sequential Multiple Assignment Randomized Trial (SMART).
smart longitudinal-data randomized-trials study-design power-calculation sample-size-estimation adaptive-interventions dispersed-count-outcome dynamic-treatment-regimens
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Feb 15, 2022 - R
Code and Datasets for the paper "Deconfounding actor-critic network with policy adaptation for dynamic treatment regimes", published on KDD 2022.
reinforcement-learning mimic-iii electronic-health-record mechanical-ventilation causal-reinforcement-learning actor-critic-model dynamic-treatment-regimens
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Feb 20, 2022 - Python
We have presented CIL method to learn the optimal dynamic treatment regime by exploiting information from both trajectories (positive and negative).
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Dec 5, 2022 - Python
Companion code for the following paper: https://doi.org/10.1093/biostatistics/kxad035
bayesian-methods biostatistics bayesian bayesian-data-analysis causal-inference dynamic-treatment-regimens
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Dec 2, 2024 - R
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