Volume 8 Number 8 (Aug. 2013)
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JSW 2013 Vol.8(8): 1923-1931 ISSN: 1796-217X
doi: 10.4304/jsw.8.8.1923-1931

Prediction of Acute Hypotensive Episode in ICU Using Chebyshev Neural Network

Yuan Zhou, Qiang Zhu, Huifang Huang

Department of Biomedical Engineering, Institute of Computer and Information Technology, Beijing Jiaotong University, Beijing, China

Abstract—An Acute Hypotensive Episode (AHE) is a serious threat to the lives of Intensive Care Unit (ICU) patients. The proposed method of accurately predicting an AHE will allow doctors to make a timely and effective intervention; therefore, it has a high clinical value. In recent years, the Chebyshev neural network model has been favorably applied in other fields. In this study, we built a Chebyshev neural network based on pattern recognition to predict AHE in ICU patients. We preprocessed the arterial blood pressure (ABP) data of the ICU patients, and then, extracted time-domain signal features from the data to construct the feature vector. We trained the neural network using a classified predictive model to predict AHEs. We used the classic BP neural network and its improved versions for comparison. Our experimental results show that our Chebyshev neural network model performs better than other solutions in predicting AHEs; therefore, it can provide a reference for clinical applications.

Index Terms—AHE prediction, Chebyshev neural network, modeling.


Cite: Yuan Zhou, Qiang Zhu, Huifang Huang, "Prediction of Acute Hypotensive Episode in ICU Using Chebyshev Neural Network," Journal of Software vol. 8, no. 8, pp. 1923-1931, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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