`Probabilistic Ensemble Learning for Prediction of Stroke Thrombectomy Outcomes from the NeuroVascular Quality Initiative - Quality Outcomes Database (NVQI-QOD) Registry.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Published Date: Jul 18, 2025

Abstract

INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke. The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-operative outcomes. Although these data are highly informative, there is substantial uncertainty in all medical interventions, so patient outcomes remain variable after intervention. In this work, we leverage a probabilistic machine learning paradigm to predict MT outcomes in the context of this inherent uncertainty.

Authors

  • Chaochao Zhou
    Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, 60611, U.S.
  • Dayeong An
    Department of Radiology, Neurology, and Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
  • Syed Hasib Akhter Faruqui
    Department of Mechanical Engineering, The University of Texas at San Antonio, San Antonio, TX, United States of America.
  • Abhinav Patel
    Department of Radiology, Neurology, and Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
  • Ramez N Abdalla
    Department of Radiology, Neurology, and Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
  • Ali Shaibani
    Department of Radiology, Neurology, and Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
  • Sameer A Ansari
    Department of Radiology, Neurology, and Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
  • Donald R Cantrell
    Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals