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

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.