The Prediction Model for High-Risk Patient with Liver Cancer Based on Classification Approaches

Cancer is an important cause of death in both male and female. An early classification of liver cancer for high-risk patients can be helpful in medical care and healthcare management. So, the requirement of this background, data mining analysis should be used to identify risk factors for assessment of cancer development. However, there has been minimal research regarding with the death in liver cancer. Therefore, we developed the prediction model to identify the high-risk patients who had liver cancer. In our experiment, Naive Bayesian model showed higher performance, as compared with other classification approaches such as Naive Bayesian, support vector machine, artificial neural network, and decision tree. We expect that the prediction model will contribute to improve efficiency in decision making for identification of high-risk patients with liver cancer.