Estimation of Warfarin Dosage with Reinforcement Learning
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Abstract (arXiv)
In this paper, it has attempted to use Reinforcement learning to model the proper dosage of Warfarin for patients.The paper first examines two baselines: a fixed model of 35 mg/week dosages and a linear model that relies on patient data. We implemented a LinUCB bandit that improved performance measured on regret and percent incorrect. On top of the LinUCB bandit, we experimented with online supervised learning and reward reshaping to boost performance. Our results clearly beat the baselines and show the promise of using multi-armed bandits and artificial intelligence to aid physicians in deciding proper dosages.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 2 references that are in the map. First posted on arXiv 15 Sep 2021.
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