Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model.

Journal: Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
PMID: 32847449

Abstract

BACKGROUND: Recently approved artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams. We performed this analysis to determine if utilization of AI software and workflow platform can reduce the transfer time (time interval between CTA at a primary stroke center (PSC) to door-in at a comprehensive stroke center (CSC)).

Authors

  • Ameer E Hassan
    Clinical Research Department, Valley Baptist Medical Center, Harlingen, TX, USA.
  • Victor M Ringheanu
    Clinical Research Department, Valley Baptist Medical Center, Harlingen, TX, USA.
  • Rani R Rabah
    Clinical Research Department, Valley Baptist Medical Center, Harlingen, TX, USA.
  • Laurie Preston
    Clinical Research Department, Valley Baptist Medical Center, Harlingen, TX, USA.
  • Wondwossen G Tekle
    Clinical Research Department, Valley Baptist Medical Center, Harlingen, TX, USA.
  • Adnan I Qureshi
    Zeenat Qureshi Stroke Institute, St. Cloud, Minnesota, USA.

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