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Individualized sepsis treatment using reinforcement learning

Nature Medicinevolume 24pages16411642 (2018) | Download Citation

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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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Author information

Affiliations

  1. Department of Computer Science and Applied Math and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA

    • Suchi Saria
  2. Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    • Suchi Saria
  3. Armstrong Institute for Patient Safety and Quality, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD, USA

    • Suchi Saria

Authors

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Competing interests

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).

Corresponding author

Correspondence to Suchi Saria.

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DOI

https://doi.org/10.1038/s41591-018-0253-x

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