Concepedia

Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning

Jianmin Ling, Tongzhou Liao, Yanqing Wu, Zhaohua Wang, Hai Jin, Feng Lu, Minghao Fang

Journal of Clinical Laboratory Analysis · 2021 · 37 citations · 41 references

DOIFull text

Open access

Abstract

Interpretable machine learning can be applied in clinical research. Elevated RDW is not only common in patients with SAT but is also associated with a poor prognosis.

References

41

The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)

Mervyn Singer, Clifford S. Deutschman, Christopher W. Seymour et al. · JAMA · 2016 · 26.3K citations · Full text

The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure

Jean‐Louis Vincent, Rui P. Moreno, Jukka Takala et al. · Intensive Care Medicine · 1996 · 11.2K citations

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From local explanations to global understanding with explainable AI for trees

Scott Lundberg, Gabriel Erion, Hugh Chen et al. · Nature Machine Intelligence · 2020 · 7.7K citations · Full text

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Neutrophil emigration in the skin, lungs, and peritoneum: different requirements for CD11/CD18 revealed by CD18-deficient mice.

PubMed · 1997 · 7.1K citations

Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units

Jean‐Louis Vincent, Arnaldo de Mendonça, F. Cantraine et al. · Critical Care Medicine · 1998 · 3.4K citations