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Toward AI-Powered Neurovascular Intervention: From Imaging to XR-Robotic Convergence.

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Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis and intervention. AI-powered tools promise more precise, accessible neurovascular treatments for better patient outcomes.

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Stroke is a major global health challenge requiring rapid diagnosis and intervention.
  • Neuroimaging techniques are crucial for identifying cerebrovascular conditions like stenosis and aneurysms.
  • Current stroke care necessitates advancements for improved patient outcomes.

Purpose of the Study:

  • To review recent advancements in artificial intelligence (AI)-augmented stroke care.
  • To explore AI applications across the stroke care continuum, from diagnosis to intervention.
  • To assess the potential and challenges of integrating AI into neurovascular interventions.

Main Methods:

  • Review of current literature on AI applications in stroke diagnosis and treatment.
  • Analysis of AI models (CNNs, transformers, LLMs) for multimodal neuroimaging analysis.
  • Examination of AI-driven planning, extended reality, and robotic platforms for intervention.

Main Results:

  • AI demonstrates significant potential in automating stroke diagnosis through image analysis and classification.
  • Emerging AI frameworks are being developed for treatment planning and robotic-assisted interventions.
  • Most AI systems are in preclinical or feasibility stages, indicating future potential.

Conclusions:

  • AI integration offers a pathway toward intelligent, multimodal platforms for stroke management.
  • Addressing translational and ethical challenges is crucial for the safe adoption of AI in neurovascular care.
  • AI advancements pave the way for precision-driven and globally accessible neurovascular interventions.