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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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Detalhes bibliográficos
Main Authors:	Liu, Nan, Koh, Zhi Xiong, Goh, Junyang, Lin, Zhiping, Haaland, Benjamin, Ting, Boon Ping, Ong, Marcus Eng Hock
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BioMed Central 2014
Assuntos:	Research Article
Acesso em linha:	https://ncbi.nlm.nih.gov/pmc/articles/PMC4150554/ https://ncbi.nlm.nih.gov/pubmed/25150702 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1472-6947-14-75
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Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

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