Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions.
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 learning. However, many challenges could affect the effectiveness of these algorithms in the real world. We provide guidelines for decision-making.
Author(s): Figueroa, Caroline A, Aguilera, Adrian, Chakraborty, Bibhas, Modiri, Arghavan, Aggarwal, Jai, Deliu, Nina, Sarkar, Urmimala, Jay Williams, Joseph, Lyles, Courtney R
DOI: 10.1093/jamia/ocab001