Early prediction of mortality of septic patients visiting emergency room using machine learning

被引：0

作者：

Heo, J. ^{[1
]}

Heo, Y. ^{[1
]}

Moon, D. H. ^{[1
]}

Bak, S. H. ^{[2
]}

Kim, W. J. ^{[1
]}

Han, S. ^{[1
]}

Choi, S. ^{[3
]}

Kim, D. ^{[3
]}

Kim, Y. ^{[3
,4
]}

Choi, H. ^{[3
,4
]}

机构：

[1] Kangwon Natl Univ, Kangwon Natl Univ Hosp, Dept Internal Med, Chunchon, South Korea

[2] Kangwon Natl Univ, Sch Med, Dept Radiol, Chunchon, South Korea

[3] ZIOVISION Co Ltd, Dept Res & Dev, Chunchon, South Korea

[4] Kangwon Natl Univ, Dept Comp Sci & Engn, Chunchon, South Korea

来源：

EUROPEAN RESPIRATORY JOURNAL | 2022年 / 60卷

关键词：

Sepsis;

D O I：

10.1183/13993003.congress-2022.3433

中图分类号：

R56 [呼吸系及胸部疾病];

学科分类号：

摘要：

3433

引用

页数：2

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