no code implementations • 22 Mar 2021 • Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand, Anna Rafferty
We therefore use our case study of the ubiquitous two-arm binary reward setting to empirically investigate the impact of using Thompson Sampling instead of uniform random assignment.
no code implementations • 30 Oct 2021 • Nina Deliu, Joseph J. Williams, Sofia S. Villar
Increasing power in such small pilot experiments, without limiting the adaptive nature of the algorithm, can allow promising interventions to reach a larger experimental phase.
no code implementations • 15 Dec 2021 • Tong Li, Jacob Nogas, Haochen Song, Harsh Kumar, Audrey Durand, Anna Rafferty, Nina Deliu, Sofia S. Villar, Joseph J. Williams
TS-PostDiff takes a Bayesian approach to mixing TS and Uniform Random (UR): the probability a participant is assigned using UR allocation is the posterior probability that the difference between two arms is 'small' (below a certain threshold), allowing for more UR exploration when there is little or no reward to be gained.
no code implementations • 4 Mar 2022 • Nina Deliu, Joseph Jay Williams, Bibhas Chakraborty
In recent years, reinforcement learning (RL) has acquired a prominent position in the space of health-related sequential decision-making, becoming an increasingly popular tool for delivering adaptive interventions (AIs).
no code implementations • 18 May 2022 • Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus
While interest in the application of machine learning to improve healthcare has grown tremendously in recent years, a number of barriers prevent deployment in medical practice.
1 code implementation • 13 Oct 2023 • Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris Karr, Theresa Nguyen, David Mohr, Anna Rafferty, Sofia Villar, Nina Deliu, Joseph Jay Williams
Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support.
no code implementations • 24 Nov 2023 • Xueqing Liu, Nina Deliu, Tanujit Chakraborty, Lauren Bell, Bibhas Chakraborty
Mobile health (mHealth) technologies aim to improve distal outcomes, such as clinical conditions, by optimizing proximal outcomes through just-in-time adaptive interventions.