Interpretable Machine Learning for Early Prediction of Prognosis in Sepsis: A Discovery and Validation Study-Reference-Cited by-同舟云学术

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Interpretable Machine Learning for Early Prediction of Prognosis in Sepsis: A Discovery and Validation Study

Published:2022-04-10 Issue:3 Volume:11 Page:1117-1132
ISSN:2193-8229
Container-title:Infectious Diseases and Therapy
language:en
Short-container-title:Infect Dis Ther

Author:

Hu Chang,Li Lu,Huang Weipeng,Wu Tong,Xu Qiancheng,Liu Juan,Hu Bo

Funder

Chinese Medical Information and Big Data Association

Translational Medicine and Interdisciplinary Research Joint Fund of Zhongnan Hospital of Wuhan University

Publisher

Springer Science and Business Media LLC

Subject

Infectious Diseases,Microbiology (medical)

Link

https://link.springer.com/content/pdf/10.1007/s40121-022-00628-6.pdf

Reference28 articles.

1. Cecconi M, Evans L, Levy M, Rhodes A. Sepsis and septic shock. Lancet. 2018;392(10141):75–87.

2. Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):801–10.

3. Xie J, Wang H, Kang Y, et al. The epidemiology of sepsis in Chinese ICUs: a national cross-sectional survey. Crit Care Med. 2020;48(3):e209–18.

4. Reinhart K, Daniels R, Kissoon N, Machado FR, Schachter RD, Finfer S. Recognizing sepsis as a global health priority—a WHO resolution. N Engl J Med. 2017;377(5):414–7.

5. Alam N, Hobbelink EL, van Tienhoven AJ, van de Ven PM, Jansma EP, Nanayakkara PW. The impact of the use of the Early Warning Score (EWS) on patient outcomes: a systematic review. Resuscitation. 2014;85(5):587–94.

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