Optimizing sepsis treatment strategies via a reinforcement learning model-Reference-Cited by-同舟云学术

Optimizing sepsis treatment strategies via a reinforcement learning model

Published:2024-01-04 Issue:2 Volume:14 Page:279-289
ISSN:2093-9868
Container-title:Biomedical Engineering Letters
language:en
Short-container-title:Biomed. Eng. Lett.

Author:

Zhang Tianyi,Qu Yimeng,wang Deyong,Zhong Ming,Cheng Yunzhang,Zhang Mingwei^ORCID

Funder

Academic Leader Program of Shanghai Public Health System Construction 3-Year Action Plan

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13534-023-00343-2.pdf

Reference27 articles.

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3. Gaieski DF, Edwards JM, Kallan MJ, et al. Benchmarking the incidence and mortality of severe sepsis in the United States. Crit Care Med. 2013. https://doi.org/10.1097/CCM.0b013e31827c09f8.

4. Levy MM, Evans LE, Rhodes A. The surviving sepsis campaign bundle: 2018 update. Intensiv Care Med. 2018. https://doi.org/10.1007/s00134-018-5085-0.

5. Jinxin Z, Kuo S, Dahai H, et al. (2022) Advances in early diagnosis and treatment of sepsis. Chinese journal of injury and repair (Electronic Edition)