Development and Validation of a Machine Learning Model to Phenotype Surgical Patients at Risk of Developing Postoperative Sepsis

被引：0

作者：

Walters, Emily ^{[1
]}

Hill, Brian ^{[1
]}

Cannesson, Maxime ^{[2
]}

机构：

[1] Univ Calif Los Angeles, Los Angeles, CA USA

[2] Univ Calif Los Angeles, David Geffen Sch Med, Los Angeles, CA 90095 USA

来源：

ANESTHESIA AND ANALGESIA | 2020年 / 130卷

关键词：

D O I：

暂无

中图分类号：

R614 [麻醉学];

学科分类号：

100217 ;

摘要：

引用

页码：959 / 959

页数：1

共 3 条

[1]

Pedregosa F, 2011, J MACH LEARN RES, V12, P2825

[2] Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis [J].

Seymour, Christopher W. ;

Kennedy, Jason N. ;

Wang, Shu ;

Chang, Chung-Chou H. ;

Elliott, Corrine F. ;

Xu, Zhongying ;

Berry, Scott ;

Clermont, Gilles ;

Cooper, Gregory ;

Gomez, Hernando ;

Huang, David T. ;

Kellum, John A. ;

Mi, Qi ;

Opal, Steven M. ;

Talisa, Victor ;

van der Poll, Tom ;

Visweswaran, Shyam ;

Vodovotz, Yoram ;

Weiss, Jeremy C. ;

Yealy, Donald M. ;

Yende, Sachin ;

Angus, Derek C. .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2019, 321 (20) :2003-2017

[3]

Singer M, 2016, JAMA-J AM MED ASSOC, V315, P801, DOI 10.1001/jama.2016.0287

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