• Ther Adv Neurol Disord · Jan 2020

    Review

    Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework.

    • Vida Abedi, Ayesha Khan, Durgesh Chaudhary, Debdipto Misra, Venkatesh Avula, Dhruv Mathrawala, Chadd Kraus, Kyle A Marshall, Nayan Chaudhary, Xiao Li, Clemens M Schirmer, Fabien Scalzo, Jiang Li, and Ramin Zand.
    • Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA.
    • Ther Adv Neurol Disord. 2020 Jan 1; 13: 1756286420938962.

    AbstractStroke is the fifth leading cause of death in the United States and a major cause of severe disability worldwide. Yet, recognizing the signs of stroke in an acute setting is still challenging and leads to loss of opportunity to intervene, given the narrow therapeutic window. A decision support system using artificial intelligence (AI) and clinical data from electronic health records combined with patients' presenting symptoms can be designed to support emergency department providers in stroke diagnosis and subsequently reduce the treatment delay. In this article, we present a practical framework to develop a decision support system using AI by reflecting on the various stages, which could eventually improve patient care and outcome. We also discuss the technical, operational, and ethical challenges of the process.© The Author(s), 2020.

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