An Ensemble Machine Learning Approach for Early Liver Disease Prediction

Liver disease is a critical global health issue that often progresses without noticeable symptoms, making early detection essential for effective treatment and prevention. This study presents a machine learning based approach for the prediction of liver disease using clinical and biochemical parameters. The dataset used includes various attributes such as age, gender, bilirubin levels, liver enzyme measurements, and protein levels,which are relevant indicators of liver function