Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learning-Reference-Cited by-同舟云学术

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Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learning

Published:2023 Issue: Volume:21 Page:2316-2331
ISSN:2001-0370
Container-title:Computational and Structural Biotechnology Journal
language:en
Short-container-title:Computational and Structural Biotechnology Journal

Author:

Ke Li,Lu Yasu^ORCID,Gao Han,Hu Chang,Zhang Jiahao,Zhao Qiuyue,Sun Zhongyi,Peng Zhiyong

Funder

National Natural Science Foundation of China

Wuhan University

Publisher

Elsevier BV

Subject

Computer Science Applications,Genetics,Biochemistry,Structural Biology,Biophysics,Biotechnology

Reference47 articles.

1. The third international consensus definitions for sepsis and septic shock (Sepsis-3);Singer;Jama-J Am Med Assoc,2016

2. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study;Rudd;Lancet,2020

3. Epidemiology of severe sepsis;Mayr;Virulence,2014

4. Sepsis: pathophysiology and clinical management;Gotts;Bmj-Brit Med J,2016

5. Severe sepsis and septic shock;Angus;N Engl J Med,2013

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