Machine learning

NeuralStroke: AI-Powered Stroke Risk Prediction 🎯 The Challenge Stroke is a leading global cause of death and disability. Early detection is complex due to multiple interacting risk factors. 💡 Our Solution An ML-based screening system that: • Analyzes 35K medical samples with 16 key features • Balances data (61.6% at-risk vs 38.4% healthy) • Applies advanced feature engineering & multiple algorithms • Achieves 96.4% precision with explainable results 🛠️ Technical Implementation • Stack: Python, Scikit-Learn, TensorFlow, Streamlit • Process: Data cleaning → EDA → Feature selection (RFE) → Model training • Validation: ROC-AUC, Classification Reports, Confusion Matrices 🏆 Results • Best model: 96.4% accuracy (Logistic Regression) • Neural Network: 95.9% accuracy with full interpretability