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pro vyhledávání: '"Hussain M Azeem"'
Autor:
Hussain M Azeem
Publikováno v:
Stroke: Vascular and Interventional Neurology, Vol 3, Iss S2 (2023)
Introduction Automated machine learning (ML)‐based large vessel occlusion (LVO) detection algorithms have been shown to improve in‐hospital workflow metrics including door to groin time (DTG). The degree to which care team engagement and interact
Externí odkaz:
https://doaj.org/article/432916d9deca464bbc499b016df2f67b
Autor:
Arash Niktabe, Juan Carlos Martinez‐Gutierrez, Sergio Salazar‐Marioni, Rania Abdelkhaleq, Juan Carlos Rodriguez Quintero, Jerome A. Jeevarajan, Muhammad Bilal Tariq, Ananya S. Iyyangar, Hussain M. Azeem, Anjan Nagesh Ballekere, Ngoc Mai Le, Louise D. McCullough, Sunil A. Sheth, Youngran Kim
Publikováno v:
Stroke: Vascular and Interventional Neurology, Vol 4, Iss 4 (2024)
Background Computed tomography perfusion (CTP) predictions of infarct core play an important role in the determination of treatment eligibility in large‐vessel occlusion acute ischemic stroke. Prior studies have demonstrated that blood glucose can
Externí odkaz:
https://doaj.org/article/a98bb1a47c294cf18f0ff9f221ac1aea
Autor:
Muhammad Bilal Tariq, Iman Ali, Sergio Salazar‐Marioni, Ananya S. Iyyangar, Hussain M. Azeem, Swapnil Khose, Victor Lopez, Rania Abdelkhaleq, Louise D. McCullough, Sunil A. Sheth, Youngran Kim
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 12, Iss 14 (2023)
Background Prehospital routing of patients with large vessel occlusion (LVO) acute ischemic stroke (AIS) to centers capable of performing endovascular therapy may improve clinical outcomes. Here, we explore whether distance to comprehensive stroke ce
Externí odkaz:
https://doaj.org/article/7750a3f65a5e4a8d9669cff0857c7ac5