1 citations · 1 across the 6 of their papers we have counts for
6 papers
Learning When to Intervene on Habitual Behaviors: A Case Study in Oral Health Care
Bhanu Teja Gullapalli, Vivek Shetty, Anna L. Trella +2
A central challenge for digital health interventions aimed at improving habitual behaviors is deciding when to deliver an intervention prompt. For many daily habits, such as tooth…
A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial
Anna L. Trella, Kelly W. Zhang, Hinal Jajal +4
Dental disease is a prevalent chronic condition associated with substantial financial burden, personal suffering, and increased risk of systemic diseases. Despite widespread recomm…
Replicable Bandits for Digital Health Interventions
Kelly W. Zhang, Nowell Closser, Anna L. Trella +1
Adaptive treatment assignment algorithms, such as bandit algorithms, are increasingly used in digital health intervention clinical trials. Frequently, the data collected from these…
Oralytics Reinforcement Learning Algorithm
Anna L. Trella, Kelly W. Zhang, Stephanie M. Carpenter +6
Dental disease is still one of the most common chronic diseases in the United States. While dental disease is preventable through healthy oral self-care behaviors (OSCB), this basi…
The Fallacy of Minimizing Cumulative Regret in the Sequential Task Setting
Ziping Xu, Kelly W. Zhang, Susan A. Murphy
Online Reinforcement Learning (RL) is typically framed as the process of minimizing cumulative regret (CR) through interactions with an unknown environment. However, real-world RL…
Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani +4
Online reinforcement learning (RL) algorithms offer great potential for personalizing treatment for participants in clinical trials. However, deploying an online, autonomous algori…