Emerging role of artificial intelligence in stroke imaging

Area of Science:

• Neurology
• Medical Informatics
• Artificial Intelligence

Background:

• Stroke diagnosis and treatment are increasingly complex due to evolving therapies and new disease-response associations.
• Clinicians require continuous learning to integrate advancements into practice.
• Artificial intelligence (AI) offers potential to standardize clinical decisions and accelerate data analysis in stroke care.

Purpose of the Study:

• To provide an updated review of artificial intelligence applications in stroke.
• To analyze recent literature on AI for stroke diagnosis and outcome prediction.

Main Methods:

• Systematic review of recent scientific papers on AI in stroke.
• Categorization of AI applications into stroke diagnosis and outcome prediction.

Main Results:

• AI can process and integrate extensive clinical and imaging data for individual patients.
• AI models, optimized with large datasets, can support clinical decision-making in stroke management.
• AI assists in predicting treatment responses and patient outcomes.

Conclusions:

• AI holds significant value in synthesizing complex patient data for improved stroke recognition and management.
• The integration of AI can enhance the accuracy of stroke diagnosis and prognosis.
• AI-driven insights are crucial for advancing personalized stroke therapy and patient outcome prediction.