An Ensemble Machine Learning Approach for Early Liver Disease Prediction

Naga Lakshmi Korrapati 1, Gangavarapu Nagireddy2, Sirigiri Karthik Kumar 3 , Torlakonda
Haribabu 4 , Dr Shaik MD Rafi 5
1B-Tech STUDENT in the Department OF IT & SRI MITTAPALLI COLLEGE OF ENGINEERING
2B-Tech STUDENT in the Department OF IT & SRI MITTAPALLI COLLEGE OF ENGINEERING
3B-Tech STUDENT in the Department OF IT & SRI MITTAPALLI COLLEGE OF ENGINEERING
4B-Tech STUDENT in the Department OF IT & SRI MITTAPALLI COLLEGE OF ENGINEERING
5Professor in the Department of Computer Science and Engineering

Abstract - 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. Thedatasetused includes various attributes such as age, gender, bilirubin levels, liver enzyme measurements, and protein levels,which are relevant indicators ofliver function.