Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

Journal: AJNR. American journal of neuroradiology
Published Date: Jan 1, 2021

Abstract

BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on the basis of machine learning algorithms for patients with acute ischemic stroke and to compare the performance between multiple models and the Stroke Prognostication Using Age and National Institutes of Health Stroke Scale (SPAN-100) index model.

Authors

  • B Jiang
    From the Department of Radiology, Neuroradiology Section (B.J., G.Z., Y.X., J.J.H., H.C., Y.L., G.Z., M.W.), Stanford University School of Medicine, Palo Alto, California.
  • G Zhu
    From the Department of Radiology, Neuroradiology Section (B.J., G.Z., Y.X., J.J.H., H.C., Y.L., G.Z., M.W.), Stanford University School of Medicine, Palo Alto, California.
  • Y Xie
    From the Department of Radiology, Neuroradiology Section (B.J., G.Z., Y.X., J.J.H., H.C., Y.L., G.Z., M.W.), Stanford University School of Medicine, Palo Alto, California.
  • J J Heit
    From the Department of Radiology, Neuroimaging, and Neurointervention Division (J.J.H.), Stanford University School of Medicine, Stanford, California jheit@stanford.edu.
  • H Chen
    Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
  • Y Li
  • V Ding
    Department of Medicine (V.D.), Quantitative Sciences Unit, Stanford University, Stanford, California.
  • A Eskandari
    Neurology Service (A.E., P.M.), Centre Hospitalier Universitaire Vaudois and Lausanne University, Lausanne, Switzerland.
  • P Michel
    Neurology Service (A.E., P.M.), Centre Hospitalier Universitaire Vaudois and Lausanne University, Lausanne, Switzerland.
  • G Zaharchuk
    From the Departments of Radiology (G.Z., M.W., D.R., C.P.L.) gregz@stanford.edu.
  • M Wintermark
    From the Departments of Radiology (G.Z., M.W., D.R., C.P.L.).

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