Deep learning on pre-procedural computed tomography and clinical data predicts outcome following stroke thrombectomy.

Journal: Journal of neurointerventional surgery
Published Date: Feb 14, 2025

Abstract

BACKGROUND: Deep learning using clinical and imaging data may improve pre-treatment prognostication in ischemic stroke patients undergoing endovascular thrombectomy (EVT).

Authors

  • James P Diprose
    Independent Computer Scientist, Auckland, New Zealand.
  • William K Diprose
    Department of Medicine, University of Auckland, Auckland, New Zealand.
  • Tuan-Yow Chien
    Independent Computer Scientist, Auckland, New Zealand.
  • Michael T M Wang
    Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
  • Andrew McFetridge
    Department of Radiology, Auckland City Hospital, Auckland, New Zealand.
  • Gregory P Tarr
    Auckland City Hospital, Auckland, New Zealand.
  • Kaustubha Ghate
    Department of Neurology, Auckland City Hospital, Auckland, New Zealand.
  • James Beharry
    Department of Neurology, Christchurch Hospital, Christchurch, New Zealand.
  • JaeBeom Hong
    Department of Neurology, Auckland City Hospital, Auckland, New Zealand.
  • Teddy Wu
    Department of Neurology, Christchurch Hospital, Christchurch, New Zealand.
  • Doug Campbell
    Department of Anaesthesia and Perioperative Medicine, Auckland City Hospital, Auckland, New Zealand.
  • P Alan Barber
    Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand a.barber@auckland.ac.nz.

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