Ensemble of Convolutional Neural Networks for StrokePrediction: Towards Improved Diagnostic Accuracy
Brain stroke, known for its high mortality and incidence rates, poses significant health risks and requires rapid intervention for survival. Early diagnosis and preventive measures can greatly reduce life loss and disabilities. Recent advancements in deep learning have led to novel computer-aided diagnostic techniques for early stroke detection. This study proposes an intelligent system that predicts potential strokes using eleven features, evaluated through seven supervised machine learning algorithms. The process includes a literature review, dataset visualization, data preprocessing, and mo
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- PossiblePossibly related (embedding) · 53%Advancing Neurological Disease Prediction through Machine Learning Techniques - The Malone Telegram →
- PossiblePossibly related (embedding) · 51%Advancing Neurological Disease Prediction through Machine Learning Techniques - Fairfax County Times →
- PossiblePossibly related (embedding) · 50%Advancing Neurological Disease Prediction through Machine Learning Techniques - True North Radio Network →
- PossiblePossibly related (embedding) · 52%Advancing Neurological Disease Prediction through Machine Learning Techniques - lincolnjournal.com →
- PossiblePossibly related (embedding) · 52%Advancing Neurological Disease Prediction through Machine Learning Techniques - Carroll County Mirror-Democrat →
- LinkedLinked via arxiv author · 85%Md Shahriar Sajid →
“Ensemble of Convolutional Neural Networks for StrokePrediction: Towards Improved Diagnostic Accuracy”
- PossiblePossibly related (embedding) · 62%Machine learning-based prediction of early neurological deterioration after stroke embolectomy - springermedicine.com →
