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Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 9)

Publication Date:

Authors : ; ;

Page : 263-269

Keywords : Hepatitis; Data Mining; NB TREE; NAÏVE BAYES; SMO;

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Hepatitis virus infection substantially increases the risk of chronic liver disease and hepatocellular carcinoma in humans and also affects majority of population in all age groups. It is the major challenge for many hospitals and public health care services for diagnosing hepatitis. Accurate diagnosis and exact prediction of the disease on time can save many patients life and there health. Hepatitis viruses are the most common cause of hepatitis in the world but other infections, toxic substances (e.g. alcohol, certain drugs), and autoimmune diseases can also cause hepatitis. Data mining is an effective tool to diagnose hepatitis and to predict result. This paper review the many data mining techniques which diagnosis hepatitis virus.

Last modified: 2014-09-15 23:31:44