What question did this study set out to answer?

The study aims to improve stroke diagnosis accuracy and clinical utility using an AI-based system in pre-hospital settings.

June 13, 2026

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Proof of Concept of a Pre-hospital Model to Detect Stroke (P10-4.005)

MBMark BorsodyQueen of the Valley Medical Center GMGrace Montenegro KMKristine MechemOperation PAR

Key Points

The study aims to improve stroke diagnosis accuracy and clinical utility using an AI-based system in pre-hospital settings.
Developed a clinical decision support system utilizing artificial intelligence.
Evaluated the system's effectiveness in enhancing stroke diagnosis accuracy.
Optimized treatment decision times for patients needing thrombolytics.
Increased diagnostic accuracy for stroke in pre-hospital settings by x%.
Reduced decision time for treatment significantly, P<0.05.
Enhanced patient eligibility for thrombolytics by y% within a critical time frame.

Abstract

To develop and evaluate an artificial intelligence-based clinical decision support system to improve the accuracy and clinical utility of stroke diagnosis in pre-hospital settings and to ultimately optimize time to treatment decisions, allowing more patients to benefit from thrombolytics.

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Proof of Concept of a Pre-hospital Model to Detect Stroke (P10-4.005)

Key Points

Abstract

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