Diagnosis of hepatitis C virus based on ID3 algorithm

Abstract

Infection with the hepatitis C virus (HCV) is what causes hepatitis C. China has one of the highest hepatitis C infection rates in the world (13%-15%), and this illness affects more than 170 million people worldwide. As a result, there is an enormous need for the diagnosis of this disease. In recent years, researchers have made significant progress in this field with different machine learning algorithms and have had the ability to make a relatively precise diagnosis. However, within the machine learning algorithms that the researchers used, decision trees, particularly the ID3(Iterative Dichotomiser 3) algorithm, have been disregarded. This paper uses this algorithm in the diagnosis of hepatitis C, aiming to test the accuracy and explore the possibility of introducing this approach into application in medicine. Empirically, the novel method of applying the ID3 algorithm in the diagnosis of hepatitis C can produce relatively accurate results compared with those traditional approaches, demonstrating that this method can be used in practice and is a powerful approach for diagnosing people who have the hepatitis C virus.