Predictive Analysis for Hepatitis and Cirrhosis Liver Disease using Machine Learning Algorithms

Liver is one among the largest organs in the human body, which implements functions like creation of some proteins, activation of enzyme’s, storing glucose, minerals etc. A variety of disorders may develop and destroy our liver due to liver disease. ML and Deep Learning algorithms are used to predict liver diseases. The proposed work has compared the classification algorithms such as Random Forest (RF) Classifier, AdaBoost (AB) Classifier, Support Vector Machine (SVM) and XGBoost (XGB) algorithm for cirrhosis dataset. The performance measure, confusion matrix and accuracy score are used to compare these algorithms, and analyse the algorithm that gives better results.