Medical Diagnosis for Liver Cancer using Classification Techniques
Abstract: The important and successful applications of data mining are in fields like business intelligence, finance, digital libraries, in other industries and sectors. One of the applications of data mining is medical diagnosis which is mostly used in research area. Medical diagnosis is the field where many researchers are concentrating. To reduce the diagnosis time and improve the diagnosis accuracy, it has become an important issue. In medical, Liver Cancer is one of the most prevalent and deadly cancers in human beings. Liver cancer is difficult to be diagnosed at an early stage due to the risk factors. Therefore, new metrologies for early Liver Cancer are needed to determine the condition of the Liver Cancer. This paper encapsulates various review and research articles on liver cancer. The main goal of this review paper is to study the related works on cancer especially liver cancer. In this paper we present an overview of the current research being carried out using the data mining techniques. Various Data classification techniques or algorithms are used to solve this issue. Some classification techniques or algorithms are Decision tree, C4.5, Association rule, Bayesian networks, Support vector Machine, K-NN, Neural networks etc.
Keywords: Data Mining, Liver cancer, Decision tree, C45, Association rule, Bayesian networks, Support vector Machine, K-NN, Neural networks, CART
How to Cite?: Reetu, Narender Kumar, "Medical Diagnosis for Liver Cancer using Classification Techniques", Volume 4 Issue 5, May 2015, International Journal of Science and Research (IJSR), Pages: 2058-2061, https://www.ijsr.net/getabstract.php?paperid=SUB154635, DOI: https://dx.doi.org/10.21275/SUB154635