In recent years, reinforcement learning (RL) has acquired a prominent position in health-related sequential decision-making problems, gaining traction as a valuable tool for delivering adaptive interventions (AIs). However, in part due to a poor …
Precision health, increasingly supported by digital technologies, is a domain of research that broadens the paradigm of precision medicine, advancing everyday healthcare. This vision goes hand in hand with the groundbreaking advent of artificial …
Reinforcement learning (RL) algorithms have been long recognized as powerful tools for optimal sequential decision making. The framework is concerned with a decision maker, the agent, that learns how to behave in an unknown environment by making …
Just-in-time adaptive interventions (JITAIs) represent an intervention design that adapts the provision and type of support over time to an individual’s changing status and contexts, intending to deliver the right support on the right occasion. As a …
The study of evidence-based dynamic treatment regimes (DTRs) comprises an important line of methodological research within the domain of personalized medicine, a medical paradigm that transitions from the one-size-fits-all ideology. In this chapter …
Low physical activity is an important risk factor for common physical and mental disorders. Physical activity interventions delivered via smartphones can help users maintain and increase physical activity, but outcomes have been mixed. Here we …
Providing behavioral health interventions via smartphones allows these interventions to be adapted to the changing behavior, preferences, and needs of individuals. This can be achieved through reinforcement learning (RL), a sub-area of machine …