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An AI Solution for Mobile Stroke Detection for TeleMedicine, Hospital and Paramedic Use

Clinical Area
Life & Health Sciences
Cardiovascular & Circulatory
Emergency/Critical Care/Trauma
Diagnostics
Digital Health
Other
College
College of Engineering (COE)
Researchers
Yilmaz, Alper
Gulati, Deepak Kumar
Licensing Manager
Hampton, Andrew
614-247-9357
hampton.309@osu.edu

T2022-039

Problem Statement:

Diagnosis of arterial occlusion and an associated stroke can be lengthy, delaying patient access to treatment. As large vessel occlusions account for 24 to 46% of acute ischemic strokes and may require treatment in a comprehensive stroke center, early diagnosis is key.

Solution:

Researchers at the Ohio State University have optimized the usage of a prehospital neurological scale to evaluate stroke severity. Using this app, one can more quickly determine a course of treatment until more comprehensive testing is completed.

Commercial Application:

In emergency scenarios, this software can accelerate stroke categorization by a variety of medical professionals. It can also be adapted to better train said professionals to recognize certain stroke characteristics