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Review
. 2020 Aug 25:13:1756286420938962.
doi: 10.1177/1756286420938962. eCollection 2020.

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

Vida Abedi  1 , Ayesha Khan  2 , Durgesh Chaudhary  2 , Debdipto Misra  3 , Venkatesh Avula  1 , Dhruv Mathrawala  3 , Chadd Kraus  4 , Kyle A Marshall  4 , Nayan Chaudhary  5 , Xiao Li  5 , Clemens M Schirmer  2 , Fabien Scalzo  6 , Jiang Li  1 , Ramin Zand  7
Affiliations
Review

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

Vida Abedi et al. Ther Adv Neurol Disord. .

Abstract

Stroke 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.

Keywords: acute stroke; artificial intelligence; cerebrovascular disease/stroke; computer aided diagnosis; ischemic stroke; machine learning; stroke diagnosis; stroke in emergency department.

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Conflict of interest statement

Conflict of interest statement: The authors declare no competing interests. NC and XL are Genentech/Roche paid employees. Genentech/Roche had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.

Figures

Figure1.
Figure1.
Key steps for a stroke ML-enabled decision support system for EDs. ED, emergency department; ML, machine learning.
See this image and copyright information in PMC

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