Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke.

Journal: BMC neurology
Published Date: May 7, 2024

Abstract

BACKGROUND: Posterior Circulation Syndrome (PCS) presents a diagnostic challenge characterized by its variable and nonspecific symptoms. Timely and accurate diagnosis is crucial for improving patient outcomes. This study aims to enhance the early diagnosis of PCS by employing clinical and demographic data and machine learning. This approach targets a significant research gap in the field of stroke diagnosis and management.

Authors

  • Ahmad A Abujaber
    Nursing Department, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar.
  • Yahia Imam
    Neurology Section, Neuroscience Institute, Hamad Medical Corporation, Doha, Qatar.
  • Ibrahem Albalkhi
    Department of Neuroradiology, Alfaisal University, Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, United Kingdom.
  • Said Yaseen
    School of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
  • Abdulqadir J Nashwan
    Nursing Department, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar. anashwan@hamad.qa.
  • Naveed Akhtar
    Neurology Section, Neuroscience Institute, Hamad Medical Corporation, Doha, Qatar.

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