Stroke Prehospital Decision Support Systems Based on Artificial Intelligence: Grey Literature Scoping Review

• Stroke is a leading cause of mortality and disability worldwide. Therefore, there is a growing interest in prehospital point-of-care stroke clinical decision support systems (CDSSs), which with improved precision can identify stroke and decrease the time to optimal treatment, thereby improving clinical outcomes. Artificial intelligence (AI) may be a route to improve CDSSs for clinical benefit. Deploying AI in the area of prehospital stroke care is still in its infancy. There are several existing systematic and scoping reviews summarizing the progress of AI methods for stroke assessment. None of these reviews include grey literature, which could be a valuable source of information, especially when analysing future research and development directions. This paper aims to use grey literature to investigate stroke assessment CDSSs based on AI. The study adheres to PRISMA guidelines and presents seven records showcasing promising technologies. These records included three clinical trials, two smartphone applications, one master thesis and one PhD dissertation, which identify electroencephalogram (EEG), video analysis and voice and facial recognition as potential data sources for early stroke identification. The integration of these technologies may offer the prospect of faster and more accurate CDSSs in the future.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Neurologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Neurology (hsv//eng)

Nyckelord

Stroke.

Clinical Decision Support Systems (CDSSs)

Grey Literature

Artificial Intelligence (AI)

Prehospital Care

Machine Learning(ML)

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