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Individualized sepsis treatment using reinforcement learning

Reinforcement learning is applied to two large databases of electronic health records for patients admitted to an intensive care unit to identify individualized treatment strategies for correcting hypotension in sepsis.

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Fig. 1: Komorowski et al. use RL to develop and validate a best-practice algorithm for vasopressor versus fluid dosing.

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Correspondence to Suchi Saria.

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S.S. has received research support from the American Heart Association (Dallas) and an honorarium from AbbVie (Chicago) and has an ownership interest in Patient Ping (Boston) and Bayesian Health (Baltimore).

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Saria, S. Individualized sepsis treatment using reinforcement learning. Nat Med 24, 1641–1642 (2018). https://doi.org/10.1038/s41591-018-0253-x

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