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International Journal For Multidisciplinary Research • Vol 7 • No 4
AI-Based Stroke Prediction Using Machine Learning: A Comparative Model Evaluation with SHAP Explainability
2025
Stroke is a major global health concern and a leading cause of mortality and long-term disability. Early detection through predictive modeling can significantly improve clinical outcomes and reduce the burden on healthcare systems. This study presents a compr…
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Machine Learning

Study of algorithms that improve automatically through experience

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance.

ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics.

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International Journal For Multidisciplinary Research • Vol 7 • No 4
AI-Based Stroke Prediction Using Machine Learning: A Comparative Model Evaluation with SHAP Explainability
2025
Stroke is a major global health concern and a leading cause of mortality and long-term disability. Early detection through predictive modeling can significantly improve clinical outcomes and reduce the burden on healthcare systems. This study presents a comprehensive machine learning approach to stroke prediction using clinical data. Three classifiers Random Forest, XGBoost, and Logistic Regression were implemented and evaluated based on accuracy, AUC, and confusion matrices. SHAP (Shapley Additive explanations) w…
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