Characterization of Elevated Tumor Markers in Diagnosis of HCC Using Data Mining Methods

Abstract

Hepatocellular carcinoma (HCC) is an abnormal condition of human liver which is diagnosed at a very advanced stage. The disease is liver disorder which can be predicted after series of clinical and laboratory and imaging studies. Hepatocellular carcinoma is the most malignant tumors which is the major cause of death and requires to be treated at early stage. The prognosis of liver disease is the reflection of both tumor characteristics like tumor size, location and tumor biology along with the degree of underlying resection. Healthcare domain generates huge data which is very complex and vast. The data contains many hidden parameters and patterns which is useful in predicting the disease. Data mining helps in recognizing these hidden patterns and arriving at the diagnosis of the disease. In this chapter the authors are concentrating on HCC tumor makers. The aim of the study is to use data mining techniques to predict the presence of tumor markers and their contribution in HCC Progression.