Patient Morality Prediction System

Developed an SVM model to predict patient mortality using a Kaggle hospital dataset, achieving 98 percent accuracy

and 99 percent F1-score.

• Cleaned data and applied EDA, PCA, and StandardScaler to preprocess features, reducing dimensionality by 30 percent.

• Built a Flask-based web interface for uploading CSV files or manual data entry, improving user accessibility.