Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections

Maria Cristina Vazquez Guilamet; Michael Bernauer; Scott T. Micek; Marin H. Kollef

doi:10.1097/MD.0000000000015276

Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections

Maria Cristina Vazquez Guilamet, Michael Bernauer, Scott T. Micek, Marin H. Kollef

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Original language	English
Article number	e15276
Journal	Medicine
Volume	98
Issue number	16
DOIs	https://doi.org/10.1097/MD.0000000000015276
State	Published - Apr 1 2019

ASJC Scopus Subject Areas

General Medicine

Keywords

bloodstream infection
machine learning
outcomes
sepsis

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10.1097/MD.0000000000015276

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title = "Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections",

keywords = "bloodstream infection, machine learning, outcomes, sepsis",

author = "Guilamet, {Maria Cristina Vazquez} and Michael Bernauer and Micek, {Scott T.} and Kollef, {Marin H.}",

note = "Publisher Copyright: Copyright {\textcopyright} 2019 the Author(s).",

year = "2019",

month = apr,

day = "1",

doi = "10.1097/MD.0000000000015276",

language = "English",

volume = "98",

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T1 - Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections

AU - Guilamet, Maria Cristina Vazquez

AU - Bernauer, Michael

AU - Micek, Scott T.

AU - Kollef, Marin H.

PY - 2019/4/1

Y1 - 2019/4/1

KW - bloodstream infection

KW - machine learning

KW - outcomes

KW - sepsis

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DO - 10.1097/MD.0000000000015276

M3 - Article

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AN - SCOPUS:85065116168

SN - 0025-7974

VL - 98

JO - Medicine

JF - Medicine

IS - 16

M1 - e15276

ER -

Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections

ASJC Scopus Subject Areas

Keywords

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