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An Integration of Decision Tree and Visual Analysis to Analyze Intracranial Pressure

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Neuroproteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1598))

Abstract

In Traumatic Brain Injury (TBI), elevated Intracranial Pressure (ICP) causes severe brain damages due to hemorrhage and swelling. Monitoring ICP plays an important role in the treatment of TBI patients because ICP is considered a strong predictor of neurological outcome and a potentially amenable method to treat patients. However, it is difficult to predict and measure accurate ICP due to the complex nature of patients’ clinical conditions. ICP monitoring for severe TBI patient is a challenging problem for clinicians because traditionally known ICP monitoring is an invasive procedure by placing a device inside the brain to measure pressure. Therefore, ICP monitoring might have a high infection risk and cause medical complications. In here, an ICP monitoring using texture features is proposed to overcome this limitation. The combination of image processing methods and a decision tree algorithm is utilized to estimate ICP of TBI patients noninvasively. In addition, a visual analytics tool is used to conduct an interactive visual factor analysis and outlier detection.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Bowie State University, 14000 Jericho Park Road, Bowie, MD, 20715, USA

    Soo-Yeon Ji

  2. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, 2800 Plymouth Road, Ann Arbor, MI, 48109, USA

    Kayvan Najarian

  3. Division of Trauma, Surgical Critical Care, Carolinas Medical Center, 1000 Blythe Blv, Charlotte, NC, 28203, USA

    Toan Huynh

  4. Department of Computer Science and Information Technology, University of the District of Columbia, 4200 Connecticut Avenue NW, Washington, DC, 20008, USA

    Dong Hyun Jeong

Authors
  1. Soo-Yeon Ji
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  2. Kayvan Najarian
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  3. Toan Huynh
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  4. Dong Hyun Jeong
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Corresponding author

Correspondence to Soo-Yeon Ji .

Editor information

Editors and Affiliations

  1. Department of Psychiatry, University of Florida McKnight Brain Institute, Gainesville, Florida, USA

    Firas H. Kobeissy

  2. Department of Cell Biology, Microbiology, & Molecular Biology, University of South Florida, Tampa, Florida, USA

    Stanley M. Stevens, Jr.

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Ji, SY., Najarian, K., Huynh, T., Jeong, D.H. (2017). An Integration of Decision Tree and Visual Analysis to Analyze Intracranial Pressure. In: Kobeissy, F., Stevens, Jr., S. (eds) Neuroproteomics. Methods in Molecular Biology, vol 1598. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6952-4_21

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  • DOI: https://doi.org/10.1007/978-1-4939-6952-4_21

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6950-0

  • Online ISBN: 978-1-4939-6952-4

  • eBook Packages: Springer Protocols

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