Artificial Intelligence-Based Brain Stroke Prediction: A Review of Machine Learning, Deep Learning, and Emerging Healthcare Technologies

This review examined recent advances in AI-based brain stroke prediction, focusing on machine learning, deep learning, medical imaging analytics, explainable AI, and privacy-preserving healthcare technologies. The literature demonstrates that AI techniques can significantly improve early stroke detection and clinical decision-making. Traditional machine learning algorithms remain effective for structured healthcare data, whereas deep learning architectures provide superior performance in medical imaging applications. However, challenges related to dataset quality, class imbalance, interpretability, privacy, and clinical validation continue to limit widespread deployment. Future research should emphasize multimodal learning, explainable AI, federated healthcare systems, and personalized medicine. The integration of these emerging technologies has the potential to transform stroke prediction from a reactive diagnostic process into a proactive and preventive healthcare framework.  

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