Machine Learning Techniques for Brain Stroke Analysis and Prediction
Published in IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON), 2024, 2024
This paper evaluates various machine learning models for brain stroke analysis and prediction, using clinical and imaging-related features. Several classifiers are compared in terms of accuracy, sensitivity, and interpretability for identifying patients at high risk.
The study underscores the potential of ML-based decision support systems in aiding early diagnosis and risk stratification for stroke, complementing traditional clinical assessment.
Recommended citation: Rabita Hasan, Sheikh Md Rabiul Islam, and Md Raihan Khan, "Machine Learning Techniques for Brain Stroke Analysis and Prediction," IEEE SPICSCON 2024.
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