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October 13, 2025

Enhancing Brain Stroke Prediction Using Machine Learning for Early Intervention

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Authors

SBSuri Babu Bokka

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Overview

Novel machine learning framework enhances stroke prediction accuracy in clinical settings, suggesting advanced intervention strategies.

Key Points

  • The proposed machine learning framework significantly improves stroke prediction accuracy, offering enhanced early intervention options.
  • Random Forest consistently outperforms other classifiers in predicting stroke events, establishing it as a top choice for healthcare applications.
  • SHAP and LIME approaches ensure interpretability in clinical decision-making, making complex models more accessible to practitioners.
  • The integration of an ensemble strategy using CATBOOST and a Stacking Classifier boosts overall predictive performance for stroke diagnosis.

Cite This Study

Suri Babu Bokka (2025) studied this question.

synapsesocial.com/papers/68ed1896f29694dd1da78e3dhttps://doi.org/10.63328/ijrdes-v7ri1p8
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Also Consider

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  5. 5Evaluating machine learning models for stroke prediction based on clinical variables2025 · 22 citations