The Role of Artificial Intelligence in Acute Ischemic Stroke Care: A Narrative Review

Acute ischemic stroke remains a leading cause of death and disability; despite time-dependent reperfusion therapies, delays in recognition, imaging interpretation, triage, and specialist access still limit timely treatment. This narrative review outlines how artificial intelligence (AI) may reduce bottlenecks across the stroke pathway. Prehospital tools include dispatcher decision support, consumer wearables, mobile assessment apps, and portable diagnostics may improve early detection and destination selection. In-hospital, AI increasingly assists neuroimaging and workflow, including intracranial hemorrhage detection, automated ASPECTS scoring, large vessel occlusion identification, and perfusion-based estimation of tissue salvageability, often shortening notification and process times. We also discuss AI-enabled risk stratification, systems-of-care coordination, and emerging uses of generative AI for documentation and communication. Key limitations include domain shift, incomplete external validation, bias and equity risks, limited explainability, alert fatigue, integration challenges, and evolving regulatory accountability. Future priorities include multimodal models, prospective implementation-focused trials, and deployment-ready solutions for diverse real-world settings.