Machine learning algorithms can predict recipient length of ICU stay from pre-operative recipient characteristics and normothermic machine perfusion data

被引：0

作者：

Shanmugarajah, K. ^{[1
]}

Wehrle, C. ^{[1
]}

Lodha, R. ^{[1
]}

Ali, K. ^{[1
]}

Cazzaniga, B. ^{[1
]}

Miyazaki, Y. ^{[1
]}

Tuul, M. ^{[1
]}

Liu, Q. ^{[1
]}

Eghtesad, B. ^{[1
]}

Kwon, D. ^{[1
]}

Aucejo, F. ^{[1
]}

Kim, J. ^{[1
]}

Schlegel, A. ^{[1
]}

Fujiki, M. ^{[1
]}

Miller, C. ^{[1
]}

Khalil, M. ^{[1
]}

Pita, A. ^{[1
]}

Hashimoto, K. ^{[1
]}

机构：

[1] Cleveland Clin, Cleveland, OH USA

来源：

LIVER TRANSPLANTATION | 2024年 / 30卷

关键词：

D O I：

暂无

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

eP-223

引用

页码：196 / 196

页数：1

共 47 条

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[10] A Machine Learning Approach to Predict the Postoperative Length of Stay After Coronary Artery Bypass Grafting Using Preoperative Characteristics
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