Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU

Abstract Background Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predict the risk of hospital death of patients...

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Bibliographic Details
Main Authors: Guilan Kong, Ke Lin, Yonghua Hu
Format: Article
Language:English
Published: BMC 2020-10-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Intensive care unit
Sepsis
Prediction model
Machine learning
In-hospital mortality
Online Access:http://link.springer.com/article/10.1186/s12911-020-01271-2

Internet

http://link.springer.com/article/10.1186/s12911-020-01271-2

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