I-Corps: Artificial Intelligence-Based Clinical Decision Support for Acute Stroke Victims

University Of California-San Diego, La Jolla CA

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a computational technology to reduce the occurrence of misdiagnosed strokes in the emergency departments of underserved hospitals. These hospitals may not have a specialized stroke center or may have limited access to stroke specialists. Emergency department physicians are challenged to identify the different symptoms of stroke and to distinguish stroke from a diverse range of diseases that have overlapping symptoms. Missed or late diagnosis of strokes result in permanent disabilities or otherwise preventable deaths and incur unnecessary treatment costs for both hospitals and patients. In addition to improving the accuracy of stroke diagnosis, a computational support system may increase the speed of diagnosis, thereby increasing the administration of time-sensitive drugs that are only effective within 3 hours of the onset of stoke symptoms. Diagnosing stroke quickly and accurately therefore improves long-term stroke patient outcomes. This I-Corps project explores the translation of developments to improve clinical decision support systems to aid acute stroke diagnosis. The technology is a real-time system that is able to quantify stroke symptoms like weakness, facial droop, and incoordination simply from video footage. The proposed technology may support diagnosis by emergency department physicians without requiring an experienced stroke specialist to be on hand. The proposed technology employs a particular set of validated and published machine learning algorithms trained on a growing dataset of video and audio recordings of stroke patients undergoing neurological exams. Results show that from just 10 seconds of video footage of stroke patients sitting passively at rest, the technology is able to detect hemiparesis with 80% accuracy, exceeding the performance of neurologists conducting a video-based assessment of stroke. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.