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

• 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: 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
• Institution: Nanyang Technological University

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)...