Analysis of High-Risk Human Papillomavirus Using Decision Tree and Apriori Algorithm

Human Papillomaviruses (HPV) are small, nonenveloped, double-stranded DNA and function as pathogens that infect epithelial surfaces of humans and animals. Undetected and left not treated, HPV can develop into cervical cancer. This study aims to distinguish different types of high-risk HPV by analyzing the DNA sequences. With Decision Tree and Apriori Algorithm, the study analyzes both common and distinctive features of HPV Type 16, 18, and 58. We concluded that with the method to distinguish different HPV types, more type-specific vaccines and treatments can be developed to treat cancers that are caused by HPV, including, but not limited to, cervical cancer and oral cancer.