A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage.

Journal: Neurosurgery
Published Date: Jul 24, 2025

Abstract

BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine learning model centered on daily transcranial Doppler ultrasound (TCD) data to predict angiographic vasospasm (AV) in the context of aneurysmal subarachnoid hemorrhage (aSAH).

Authors

  • Rajeev D Sen
    Department of Neurological Surgery, New York University Langone Medical Center, New York, New York, USA.
  • Margaret C McGrath
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • Varadaraya S Shenoy
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • R Michael Meyer
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • Christine Park
    School of Medicine, Duke University, Durham, NC, USA.
  • Christine T Fong
    Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA.
  • Abhijit V Lele
    Departments of Anesthesiology, Neurology and Neurological Surgery, Harborview Medical Center, University of Washington, Seattle, Washington, USA.
  • Louis J Kim
    Department of Neurological Surgery, University of Washington, Seattle, Washington, USA.
  • Michael R Levitt
    Department of Neurological Surgery, University of Washington, Seattle, WA, USA; Departments of Radiology, Neurology, Mechanical Engineering, and Stroke & Applied Neuroscience Center, University of Washington, Seattle, WA, USA. Electronic address: mlevitt@uw.edu.
  • Lucy Lu Wang
    Allen Institute for Artificial Intelligence, Seattle, WA, United States.
  • Laligam N Sekhar
    Department of Neurosurgery, University of Washington, Seattle, Washington, USA. Electronic address: lsekhar@uw.edu.

Keywords

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