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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. � 2020, Springer Nature Switzerland AG.

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the process of identifying patterns in huge datasets comprising methods such as machine learning, statistics, and database system can beconsidered data mining. It is a multidisciplinary field in computer science and it excerpts knowledge from the massive data set and converts 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 that precisely governs the working of liver and intern affecting other organs in the body. Data mining classification techniques like Decision Tree, Linear Discriminant, SVM Fine Gaussian and Logistic Regression 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. MATLAB2016 is used in this paperfor implementing classification algorithm on the dataset. Linear Discriminant algorithm showed the highest prediction accuracy 95.8% and ROC is 0.93. � 2018 IEEE.

Liver Cancer is one of the serious disorders which when not diagnosed on time may lead to death. Hepatocellular Carcinoma (HCC) is malignant tumor which needs to be treated with priority. HCC is diagnosed generally when it reaches more progressive stage. HCC is diagnosed starting with the clinical trials, laboratory studies, tumor grading, imaging studies depending on the symptoms exhibited by the patient. Medical data contains massive hidden parameters which can be analyzed using machine learning algorithms. The current work focusses on study of various previous studies carried out in prediction of HCC using machine learning techniques like classification, regression and artificial neural networks. � 2020 IEEE.