Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.

Journal: Journal of the American Heart Association
PMID: 38874054

Abstract

BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared with prehospital stroke scales for LVO prediction.

Authors

  • Muath Alobaida
    Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital Liverpool UK.
  • Martha Joddrell
    Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital Liverpool UK.
  • Yalin Zheng
    Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom.
  • Gregory Y H Lip
    Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, L69 3BX Liverpool, UK.
  • Fiona J Rowe
    Institute of Population Health, University of Liverpool Liverpool UK.
  • Wahbi K El-Bouri
    Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital Liverpool, UK.
  • Andrew Hill
    Department of Computer Science and Engineering, University of Colorado Denver, Denver, CO 80204, USA.
  • Deirdre A Lane
    Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital Liverpool UK.
  • Stephanie L Harrison
    Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital Liverpool UK.

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