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Network-based prediction of major adverse cardiac events in acute coronary syndromes from imbalanced EMR data

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收录情况： ◇ EI

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机构： [a]IBM Research,Beijing, China [b]Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing, China [c]Department of Cardiology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan, China [d]Department of Computing, The Hong Kong Polytechnic University, Hong Kong

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关键词： Acute coronary syndrome Algorithms Machine learning

摘要：

The low proportion and the rapid evolvement of major adverse cardiac events (MACE) present challenges for predicting MACE by machine learning models. In this paper, we propose a method to predict MACE from large-scale imbalanced EMR data by using a network-based one-class classifier. It only used the reliably known MACE samples to establish the hyperspherical model. Experiments show that our model outperforms the state-of-the-art models. © 2019 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

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第一作者机构： [a]IBM Research,Beijing, China [*1]IBM Research, Software Park, Haidian District, Beijing, China, 100193.

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通讯机构： [a]IBM Research,Beijing, China [*1]IBM Research, Software Park, Haidian District, Beijing, China, 100193.

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