Monkeypox Detection with K-mer Using Machine Learning Algorithms
2nd International Conference on Science, Engineering Management and Information Technology, SEMIT 2023, Ankara, Turkey, 14 - 15 September 2023, vol.2198 CCIS, pp.111-122, (Full Text)
- Publication Type: Conference Paper / Full Text
- Volume: 2198 CCIS
- Doi Number: 10.1007/978-3-031-72284-4_7
- City: Ankara
- Country: Turkey
- Page Numbers: pp.111-122
- Keywords: HPV, k-mer, Machine Learning, Monkeypox
- Ankara Yıldırım Beyazıt University Affiliated: Yes
Abstract
According to data of World Health Organization, since 2022, Monkeypox cases have been more common around the world, including Europe and America, compared to previous years. Like every disease, correct diagnosis of Monkeypox is very important in terms of treatment and recovery period. In the clinic, Monkeypox and warts are sometimes confused with each other because they have similar symptoms. For this purpose HPV (Human papilloma virus) DNA which causes warts and Monkeypox virus DNA which causes Monkeypox, were selected in our study. Today, the rapid development of technology allows us to use technology in many areas. The progress in artificial intelligence, especially in the last 20 years, has enabled the use of artificial intelligence in both research and clinics in the field of medicine, as well as in many other fields. In our study, the full genome sequences of Monkeypox virus and HPV were used to classify these two viruses with supervised machine learning algorithms. As for features, the data obtained by calculating the number of k-mers (4-mer, 5-mer, 6-mer), which is an alignment free approach, and dividing by the full genome length (number of base pairs) for each virus, was used. According to the classification results, an accuracy of 99% or more was achieved. As a result, these two diseases were successfully distinguished using whole genome virus DNAs.