Comparison of some control strategies for three-compartment PK/PD models

By Chuanpu Hu, W. Lovejoy, S. Shafer. 1994

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Chao Yu
2. Jiming Liu
3. Adam E. Gaweda
4. Shamim Nemati
5. Brett L. Moore
6. Larry D. Pyeatt
7. Anthony G. Doufas
8. George R. Aronoff

Citations in the corpus

• Reinforcement Learning in Healthcare: A Survey (2019, methodology): “[86] studied the problem of anesthesia control by applying some of the fundamental principles of RL (the MDP formulation and its planning solutions).”
• Reinforcement learning approach to individualization of chronic pharmacotherapy (2005, unknown): “Another examples include theworksofHuetal.[8], [ 9 ].”
• Incorporating prior knowledge into Q-learning for drug delivery individualization (2005, background): “Several authors have advocated the use of techniques underlying the RL to medical decision making [1], [5], [4] over the years.”
• Reinforcement learning for closed-loop propofol anesthesia: a study in human volunteers (2014, background): “Furthermore, the basic principles of reinforcement learning (dynamic programming and value function optimization) have been studied in depthof-anesthesia control with favorable results (Hu et al., 1994).”