Abstract
Acute Hypotensive Episodes (AHE) is one of the hemodynamic instabilities with high mortality rate that is common among patients. Timely and rapid intervention is necessary to save patient’s life. This paper presents a methodology to predict AHE for ICU patients based on the Multi Genetic Programming (Multi GP). The methodology is applied to the dataset obtained from Multi-parameter Intelligent Monitoring for Intensive Care (MIMIC-II). The achieved accuracy of the proposed methodology is 79.07 % in the training set and 77.98 % in the testing set with the five-fold cross-validation.
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Acknowledgements
The authors would like to thank anonymous reviewers for their very detailed and helpful review. This work was supported by National Natural Science Foundation of China (No.: 61502291), Natural Science Foundation of Guangdong Province (No.: S2013010013974), in part by the Shantou University National Foundation Cultivation Project (No.: NFC13003).
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Jiang, D., Hu, B., Wu, Z. (2016). Predicting Acute Hypotensive Episodes Based on Multi GP. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_16
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DOI: https://doi.org/10.1007/978-981-10-0356-1_16
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