Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

Journal: World neurosurgery
PMID: 31295616

Abstract

BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.

Authors

  • Michael A Silva
    Department of Neurosurgery, Jackson Memorial Hospital, Miami, Florida, USA.
  • Jay Patel
    Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.
  • Vasileios Kavouridis
    Departments of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Troy Gallerani
    Departments of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Andrew Beers
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
  • Ken Chang
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.
  • Katharina V Hoebel
    Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.
  • James Brown
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
  • Alfred P See
    Departments of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • William B Gormley
    Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Mohammad Ali Aziz-Sultan
    Departments of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Jayashree Kalpathy-Cramer
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.
  • Omar Arnaout
    Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. Electronic address: oarnaout@bwh.harvard.edu.
  • Nirav J Patel
    Departments of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA; Computational Neuroscience Outcomes Center, Brigham and Women's Hospital, Boston, Massachusetts, USA. Electronic address: npatel40@bwh.harvard.edu.

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