Dynamic treatment regime

In medical research, a dynamic treatment regime (DTR), adaptive intervention, or adaptive treatment strategy is a set of rules for choosing effective treatments for individual patients.^[1] Historically, medical research and the practice of medicine tended to rely on an acute care model for the treatment of all medical problems, including chronic illness.^[2] Treatment choices made for a particular patient under a dynamic regime are based on that individual's characteristics and history, with the goal of optimizing his or her long-term clinical outcome. A dynamic treatment regime is analogous to a policy in the field of reinforcement learning, and analogous to a controller in control theory. While most work on dynamic treatment regimes has been done in the context of medicine, the same ideas apply to time-varying policies in other fields, such as education, marketing, and economics.^{[citation needed]}

See also

• Personalized medicine
• Reinforcement learning
• Q learning
• Optimal control
• Multi-armed bandit