Utilizing imaging parameters for functional outcome prediction in acute ischemic stroke: A machine learning study.

Journal: Journal of neuroimaging : official journal of the American Society of Neuroimaging
PMID: 38430467

Abstract

BACKGROUND AND PURPOSE: We aimed to predict the functional outcome of acute ischemic stroke patients with anterior circulation large vessel occlusions (LVOs), irrespective of how they were treated or the severity of the stroke at admission, by only using imaging parameters in machine learning models.

Authors

  • Burak B Ozkara
    Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA.
  • Mert Karabacak
    Department of Neurosurgery, Mount Sinai Health System, New York, New York, USA.
  • Meisam Hoseinyazdi
    Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Samir A Dagher
    Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA.
  • Richard Wang
    Department of Materials, Department of Bioengineering and Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, UK.
  • Sadik Y Karadon
    School of Medicine, Manisa Celal Bayar University, Manisa, Turkey.
  • F Eymen Ucisik
    Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA.
  • Konstantinos Margetis
    Department of Neurosurgery, Mount Sinai Health System, New York, New York, USA.
  • Max Wintermark
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Vivek S Yedavalli
    Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins Hospital, Baltimore, Maryland, USA.

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