# Oralytics Reinforcement Learning Algorithm

arXiv: https://arxiv.org/abs/2406.13127 · HTML: https://mlsanity.com/paper/2406.13127/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in RL for clinical treatment and surgery, one of 15 directions in Deep reinforcement learning methods.
- Builds on 13 of its 27 references that are in the map.
- First posted on arXiv 19 Jun 2024.

## Placed in

- Deep reinforcement learning methods / [RL for clinical treatment and surgery](https://mlsanity.com/deeprl/rl-for-clinical-treatment-and-surgery/)

## Builds on (most cited first, 13 of 13)

- [A Tutorial on Thompson Sampling](https://mlsanity.com/paper/1707.02038/) (2017)
- [Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity](https://mlsanity.com/paper/1909.03539/) (2019)
- [Inference for Batched Bandits](https://mlsanity.com/paper/2002.03217/) (2020)
- [Multi-Task Learning for Contextual Bandits](https://mlsanity.com/paper/1705.08618/) (2017)
- [Accurate Inference for Adaptive Linear Models](https://mlsanity.com/paper/1712.06695/) (2017)
- [A Reinforcement Learning System to Encourage Physical Activity in Diabetes Patients](https://mlsanity.com/paper/1605.04070/) (2016)
- [A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms](https://mlsanity.com/paper/2106.02126/) (2021)
- [IntelligentPooling: Practical Thompson Sampling for mHealth](https://mlsanity.com/paper/2008.01571/) (2020)
- [Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines](https://mlsanity.com/paper/2206.03944/) (2022)
- [Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care](https://mlsanity.com/paper/2208.07406/) (2022)
- [Statistical Inference After Adaptive Sampling for Longitudinal Data](https://mlsanity.com/paper/2202.07098/) (2022)
- [Horde of Bandits using Gaussian Markov Random Fields](https://mlsanity.com/paper/1703.02626/) (2017)
- [Group-driven Reinforcement Learning for Personalized mHealth Intervention](https://mlsanity.com/paper/1708.04001/) (2017)

## Built on by (most cited first, 2 of 2)

- [Stable Thompson Sampling: Valid Inference via Variance Inflation](https://mlsanity.com/paper/2505.23260/) (2025)
- [Uncertainty-Aware Selection of Online Algorithms with Simulator Ensembles](https://mlsanity.com/paper/2609.32170/) (2026)

## Abstract (arXiv)

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 basic behavior is not consistently practiced. We have developed Oralytics, an online, reinforcement learning (RL) algorithm that optimizes the delivery of personalized intervention prompts to improve OSCB. In this paper, we offer a full overview of algorithm design decisions made using prior data, domain expertise, and experiments in a simulation test bed. The finalized RL algorithm was deployed in the Oralytics clinical trial, conducted from fall 2023 to summer 2024.