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Purpose of Review <p>This review aims to provide an overview of how artificial intelligence (AI) is being integrated into stroke care across the full clinical spectrum with emphasis on its applications in diagnosis, management, and rehabilitation. The focus is on recent advances (2020–2025), addressing key questions on clinical utility and implementation challenges.</p> Recent Findings <p>AI has shown promise in enhancing stroke diagnosis through imaging analysis, wearable sensors, and remote monitoring. In stroke management, it supports decision-making and therapy optimization. AI-enabled tools are also improving rehabilitation via robotics and computer vision, and aid prevention through risk prediction and community screening. However, challenges remain in model generalizability, acceptance by the community, and ethical concerns.</p> Summary <p>AI is reshaping stroke care by enabling personalized, timely, and data-driven approaches which can significantly improve quality of life. Future progress will depend on transparent multimodal, globally validated models, supported by interdisciplinary collaboration.</p>

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Redefining Stroke Care with Artificial Intelligence: Recent Advances

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Shivi Mendiratta,
  • Mark Parsons,
  • Carlos Garcia-Esperon,
  • Amit Mehndiratta

摘要

Purpose of Review

This review aims to provide an overview of how artificial intelligence (AI) is being integrated into stroke care across the full clinical spectrum with emphasis on its applications in diagnosis, management, and rehabilitation. The focus is on recent advances (2020–2025), addressing key questions on clinical utility and implementation challenges.

Recent Findings

AI has shown promise in enhancing stroke diagnosis through imaging analysis, wearable sensors, and remote monitoring. In stroke management, it supports decision-making and therapy optimization. AI-enabled tools are also improving rehabilitation via robotics and computer vision, and aid prevention through risk prediction and community screening. However, challenges remain in model generalizability, acceptance by the community, and ethical concerns.

Summary

AI is reshaping stroke care by enabling personalized, timely, and data-driven approaches which can significantly improve quality of life. Future progress will depend on transparent multimodal, globally validated models, supported by interdisciplinary collaboration.