Mohammed Sakib Hasan: We Propose Innovative AI-Driven Solutions for Real-Time Stroke Prediction
Mohammed Sakib Hasan, Assistant General Secretary (Academic Research And Higher Studies) at CSE Club, PSTU, shared on LinkedIn about a recent article he and his colleagues co-authored, published in IEEE Xplore, adding:
”Alhamdulillah!
Our research paper, ‘StrokeGuardian: Hybrid Ensemble ML for Real-Time Brain Stroke Prediction and Clinical Decision Support,’ has been published at IEEE WIECON-ECE 2025.
Our proposed hybrid ensemble model combines Neural Networks, SVM, and XGBoost to deliver highly accurate and explainable stroke risk prediction, achieving 99.15% accuracy and 0.9979 ROC-AUC.
The system also includes a cloud-based clinical decision support platform for real-time healthcare applications.”
Title: StrokeGuardian: Hybrid Ensemble ML for Real-Time Brain Stroke Prediction and Clinical Decision Support
Authors: Mohammed Sakib Hasan, Abdul Jobayer, Jihadul Islam, Sanjida Islam Nuha, Golam Muradul Bashir
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