Analysis of Hepatitis C Virus using Data Mining Algorithm -Apriori, Decision Tree
Ha Yeong Jeong and Tae Seon Yoon,
Hankuk Academy of Foreign Studies, Republic of Korea
ABSTRACT
Hepatitis C, which presents with symptoms such as acute fatigue and jaundice, is highly likely to become
chronic, and is the main cause of liver cancer, attracting much public attention. Moreover, the number of
infected people is increasing worldwide nowadays. However, we found that there are 6 different genotype
in hcv. In vaccine and medicine developing for viruses, analysis of them is most important. Therefore, we
decided to compare 6 genotype using Apriori algorithm and Decision tree algorithm. We tried to find out
some difference between genotype 1 and others by analyzing the genotype 1, since genotype 1 is most
common, and tried to find out the correlation between the genotype 1b and 2a with the highest number of
infections in Korea. With these algorithm, we were able to find several rules and differences between them.
KEYWORDS
Hepatitis C virus, Apriori algorithm, Decision tree algorithm, virus, Bioinformatics.
https://wireilla.com/papers/ijbb/V7N3/7317ijbb01.pdf
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