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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Bibliographic Details
Main Authors: Liu, Nan, Koh, Zhi Xiong, Goh, Junyang, Lin, Zhiping, Haaland, Benjamin, Ting, Boon Ping, Ong, Marcus Eng Hock
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2014
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Online Access: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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