Forecasting Chronic Kidney Disease Using Ensemble Machine Learning Technique

India is a rapidly expanding nation on global scale. Chronic kidney disease (CKD) prevalent health problem internationally, and advance perception of this can aid prevent its stream. This research proposes an ensemble learning technique that combines three different algorithms, Logistic Regression, Gradient Boosting Random Forest for the prediction CKD. The performance each algorithm was judged based Root Mean Square Error (RMSE) (MSE) as metrics, predictions were combined using technique. dataset used study contained data 400 individuals with 24 features, which pre-processed by removing missing values normalizing data. showed better RMSE 0.2111 MSE 0.0446, compared to individual algorithms. proposed be utilized divining outcomes work reveal effectiveness potential improving patient preventing progression Additionally, applied other predictive tasks improve performance, indicating broader applicability.