Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

Background The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE)...

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Bibliografische gegevens
Hoofdauteurs: Liu, Nan, Koh, Zhi Xiong, Goh, Junyang, Lin, Zhiping, Haaland, Benjamin, Ting, Boon Ping, Ong, Marcus Eng Hock
Andere auteurs: School of Electrical and Electronic Engineering
Formaat: Journal Article
Taal:English
Gepubliceerd in: 2014
Onderwerpen:
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Online toegang:https://hdl.handle.net/10356/102512
http://hdl.handle.net/10220/24264

Internet

https://hdl.handle.net/10356/102512
http://hdl.handle.net/10220/24264

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