Intracranial Pressure Forecasting in Children Using Dynamic Averaging of Time Series Data

Akram Farhadi, Joshua J. Chern, Daniel Hirsh, Tod Davis, Mingyoung Jo, Frederick Maier and Khaled Rasheed
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Akram Farhadi: Department of Computer Science, University of Georgia, Athens, GA 30602, USA
Joshua J. Chern: Children’s Healthcare of Atlanta, Atlanta, GA 30329, USA
Daniel Hirsh: Children’s Healthcare of Atlanta, Atlanta, GA 30329, USA
Tod Davis: Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
Mingyoung Jo: Children’s Healthcare of Atlanta, Atlanta, GA 30329, USA
Frederick Maier: Institute for Artificial Intelligence, University of Georgia, Athens, GA 30602, USA
Khaled Rasheed: Department of Computer Science, University of Georgia, Athens, GA 30602, USA

Forecasting, 2018, vol. 1, issue 1, 1-12

Abstract: Increased Intracranial Pressure (ICP) is a serious and often life-threatening condition. If the increased pressure pushes on critical brain structures and blood vessels, it can lead to serious permanent problems or even death. In this study, we propose a novel regression model to forecast ICP episodes in children, 30 min in advance, by using the dynamic characteristics of continuous intracranial pressure, vitals and medications during the last two hours. The correlation between physiological parameters, including blood pressure, respiratory rate, heart rate and the ICP, is analyzed. Linear regression, Lasso regression, support vector machine and random forest algorithms are used to forecast the next 30 min of the recorded ICP. Finally, dynamic features are created based on vitals, medications and the ICP. The weak correlation between blood pressure and the ICP (0.2) is reported. The Root-Mean-Square Error (RMSE) of the random forest model decreased from 1.6 to 0.89% by using the given medication variables in the last two hours. The random forest regression gave an accurate model for the ICP forecast with 0.99 correlation between the forecast and experimental values.

Keywords: time series; sliding window; forecasting; regression; intracranial pressure (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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