Revolutionizing Acute Stroke Care: A Review of Food and Drug Administration-Approved Software as Medical Devices for Stroke Triage

Stroke remains a critical global health challenge, with ischemic stroke comprising most cases and necessitating rapid, effective treatment to improve patient outcomes. This review explores the integration of artificial intelligence (AI) and machine learning into medical devices for stroke triaging, highlighting their impact on reducing notification times, latency in care, and health disparities. By analyzing Food and Drug Administration-approved AI-enabled devices under the “Radiological computer-assisted triage and notification software” regulation category, we assess their sensitivity, specificity, and time-to-notification as the measure of their overall effectiveness in clinical settings.

The review identifies 29 such devices, examining their technological capabilities, notification methods, and performance metrics. Despite the promising advances, challenges remain in the regulatory landscape and real-world application of these technologies. Collaborative efforts among technology developers, healthcare providers, and policymakers are essential for the successful integration of AI in stroke care to ensure improved patient outcomes and equitable access to advanced medical technologies.