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Predicting Acute Hypotensive Episodes Based on Multi GP

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Computational Intelligence and Intelligent Systems (ISICA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

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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Authors and Affiliations

  1. Department of Computer Science, Shantou University, Shantou, 515063, China

    Dazhi Jiang & Bo Hu

  2. State Key Lab of Software Engineering, Computer School, Wuhan University, Wuhan, 430072, China

    Zhijian Wu

Authors
  1. Dazhi Jiang
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  2. Bo Hu
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  3. Zhijian Wu
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Corresponding author

Correspondence to Zhijian Wu .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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© 2016 Springer Science+Business Media Singapore

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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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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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