An active learning framework for enhancing identification of non-artifactual intracranial pressure waveforms.

Journal: Physiological measurement
PMID: 30562165

Abstract

OBJECTIVE: Intracranial pressure (ICP) is an important and established clinical measurement that is used in the management of severe acute brain injury. ICP waveforms are usually triphasic and are susceptible to artifact because of transient catheter malfunction or routine patient care. Existing methods for artifact detection include threshold-based, stability-based, or template matching, and result in higher false positives (when there is variability in the ICP waveforms) or higher false negatives (when the ICP waveforms lack complete triphasic components but are valid).

Authors

  • Murad Megjhani
    Department of Neurology, Columbia University, New York, NY, USA.
  • Ayham Alkhachroum
  • Kalijah Terilli
  • Jenna Ford
  • Clio Rubinos
  • Julie Kromm
  • Brendan K Wallace
  • E Sander Connolly
    Department of Neurosurgery, Columbia University, College of Physicians and Surgeons, New York, USA.
  • David Roh
  • Sachin Agarwal
    Department of Neurology, Columbia University, New York, NY, USA.
  • Jan Claassen
    Department of Neurology, Columbia University, New York, NY, USA.
  • Raghav Padmanabhan
  • Xiao Hu
    Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, United States.
  • Soojin Park
    Department of Neurology, Department of Biomedical Informatics, Columbia University, New York, NY, USA.

Keywords

External Resources

Popular Topics
Recent Journals