Design Patterns for Personalization of Healthcare Process

Vatian, Aleksandra; Dudorov, Sergey; Ивченко, Александр Владимирович; Smirnov, Kirill V.; Chikshova, Ekaterina; Lobantsev, Artem; Parfenov, Vladimir; Shalyto, Anatoly; Gusarova, Natalia

doi:10.1145/3318236.3318249

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Cited by 6 publications

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“…This technique relies on generalization and profiling to make specific assumptions about the individual based on their characteristics. Additional applications of personalization include: web content personalization and layout customization [8], [30]; customercentric interaction with their healthcare providers [19], [38]; personalized medical treatments [3], [10]; and music, video, and movie recommender systems [40].…”

Section: Introductionmentioning

confidence: 99%

On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks

Dereventsov¹,

Vatsavai²,

Webster³

2021

Preprint

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In this effort we consider a reinforcement learning (RL) technique for solving personalization tasks with complex reward signals. In particular, our approach is based on state space clustering with the use of a simplistic k-means algorithm as well as conventional choices of the network architectures and optimization algorithms. Numerical examples demonstrate the efficiency of different RL procedures and are used to illustrate that this technique accelerates the agent's ability to learn and does not restrict the agent's performance.

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