The genetic algorithm for breast tumor diagnosis—The case of DNA viruses

The purpose of this study is to determine the bioinformatics between breast tumors and DNA viruses. To extract significant factors for breast tumors, two methods – analysis of variance (ANOVA) and information measurement – are used; then, the results show that human papillomavirus (HPV) is not significant factor. Further, genetic algorithm (GA)-based data mining was submitted to obtain the rule between other DNA viruses and breast cancer/fibroadenoma. The GA rule shows that the effect of breast cancer includes {herpes simplex virus (HSV)-1 (−), human herpesvirus (HHV)-8 (−,+)}, {HSV-1(−)}, or {HHV-8(−)}, and that the effect of fibroadenoma includes {HSV-1(+), HHV-8(+)}, {HSV-1(+)}, or {HHV-8(+)}. Furthermore, the Mantel–Haenszel test shows that GA rules make a distinction between breast cancer and fibroadenoma. Finally, regarding diagnosis cost and accuracy, this study suggests that considering HSV-1 alone or with HHV-8 is optimal, but considering only HHV-8 yields less accurate results.