Analysis of Liver Disease and HCC Inducing Factors Using Machine Learning Algorithms

Abstract

The process of identifying patterns in huge datasets comprising methods such as machine learning, statistics, and database system can be considered for data mining. It is a multidisciplinary field in computer science and it excerpts knowledge from the massive data set and converts it into comprehensible format. The Medical environment is rich in information but weak in knowledge. Medical systems contain wealth of data which require a dominant analysis tool for determining concealed association and drift in data. The health care condition that comprehends to liver disorder is termed as Liver disease. Liver disorder leads to abrupt health status like Hepatocellular Carcinoma (HCC) that precisely governs the working of liver and intern affecting other organs in the body. Machine learning techniques can be used to get the result of a test with indistinguishable degree of accuracy. Data mining classification techniques like Decision Tree, Support Vector Machine Fine Gaussian and Linear Discriminant algorithms are applied. Laboratory parameters of the patients are used as the dataset. Data contains features that can establish a rigorous model using Classification technique. Linear Discriminant algorithm showed the highest prediction accuracy 95.8% and ROC is 0.93.