The treatment of sepsis: an episodic memory-assisted deep reinforcement learning approach-Reference-Cited by-同舟云学术

The treatment of sepsis: an episodic memory-assisted deep reinforcement learning approach

Published:2022-08-30 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Liang Dayang,Deng Huiyi,Liu Yunlong^ORCID

Funder

Innovation Strategy Research Program of Fujian Province

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-04099-7.pdf

Reference44 articles.

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3. Cohen J, Vincent J-L, Adhikari NKJ, Machado FR, Angus DC, Calandra T, Jaton K, Giulieri S, Delaloye J, Opal S, Tracey K, van der Poll T, Pelfrene E (2006) Sepsis: a roadmap for future research. Lancet Infect Dis 15(5):581614

4. Rhodes A, Evans LE, Alhazzani W, Levy MM, Antonelli M, Ferrer R, Kumar A, Sevransky JE, Sprung CL, Nunnally ME, Rochwerg B, Rubenfeld GD, Angus DC, Annane D, Beale RJ, Bellinghan GJ, Bernard GR, Chiche JD, Coopersmith C et al (2017) Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016. Intensive Care Med 43(3):304–377

5. Komorowski M, Celi LA, Badawi O, Gordon AC, Faisal AA (2018) The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care. Nat Med 24(11):1716–1720

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