Artificial Intelligence and Emerging Digital Technologies Across the Stroke Continuum: From Risk Prediction to...

Area of Science:

• Neurology
• Digital Health
• Medical Technology

Background:

• Stroke is a major global cause of death and disability.
• Effective prevention and early management strategies are critical.
• Emerging technologies offer new avenues for stroke care.

Purpose of the Study:

• To explore the role of emerging technologies in stroke prevention and early management.
• To review advancements in AI, wearables, digital health, and drone systems for stroke care.
• To assess the current status and future potential of these technologies.

Main Methods:

• Review of current literature on artificial intelligence (AI), wearable devices, digital health, and drone-assisted systems in stroke.
• Analysis of applications in primary, secondary, and acute stroke prevention and management.
• Evaluation of the predictive accuracy, clinical integration, and validation status of these technologies.

Main Results:

• Machine learning models show high predictive accuracy for primary stroke risk but require external validation.
• Wearables and digital devices facilitate continuous monitoring and behavioral interventions.
• AI tools aid in predicting recurrence, identifying risk factors, and improving medication adherence.
• AI-assisted neuroimaging is integrated into clinical workflows for rapid triage.
• Drone systems show potential for reducing prehospital delays, though stroke-specific evidence is limited.

Conclusions:

• Emerging technologies offer significant potential to improve stroke prevention and care continuum.
• Further prospective validation and real-world effectiveness studies are essential.
• Integration into clinical workflows is necessary for widespread implementation.