A comprehensive review for machine learning based human papillomavirus detection in forensic identification with multiple medical samples

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Abstract

Human papillomavirus (HPV) is a sexually transmitted virus. Cervical cancer is one of the highest incidences of cancer, almost all patients are accompanied by HPV infection. In addition, the occurrence of a variety of cancers is also associated with HPV infection. HPV vaccination has gained widespread popularity in recent years with the increase in public health awareness. In this context, HPV testing not only needs to be sensitive and specific but also needs to trace the source of HPV infection. Through machine learning and deep learning, information from medical examinations can be used more effectively. In this review, we discuss recent advances in HPV testing in combination with machine learning and deep learning.

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APA

Yao, H., & Zhang, X. (2023). A comprehensive review for machine learning based human papillomavirus detection in forensic identification with multiple medical samples. Frontiers in Microbiology. Frontiers Media SA. https://doi.org/10.3389/fmicb.2023.1232295

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