Junyang Goh

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  • Nan Liu, Zhi Koh, Xiong, Junyang Goh, Zhiping Lin, Benjamin Haaland +16 others
  • 2016
(2014). Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection. BMC medical informatics and decision making, 14(1), 75-. permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain(More)
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) using clinical signs and heart rate variability. METHODS(More)
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