Hepatitis Disease Diagnosis Using Backpropagation and the Naive Bayes Classifiers

Bekir Karlik

Abstract


This study presents a comparison between Backpropagation
and Naive Bayes Classifiers to diagnose hepatitis disease. Hepatitis is the general term for inflammation of the liver. The most common causes of hepatitis are the hepatotropic viruses (such as hepatitis A, B, and C) and alcohol abuse. In practice, both of these methods often compete well with more sophisticated classifiers. The performances of proposed methods
are selected for each of classification tasks of hepatitis diseases. The over-all accuracy of diagnosis systems were 98% and 97% respectively.

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