A multi-class prediction model for liver cirrhosis survival and transplant outcomes, built with ensemble learning on engineered clinical features.
A Kaggle competition entry built for fun in spare time — a multi-class classification model predicting cirrhosis patient survival and transplant outcomes, using ensemble methods (XGBoost/LightGBM) on top of engineered clinical features.