一篇综合评述：基于机器学习的多样医学样本在法医鉴定中用于人类乳头瘤病毒检测。
A comprehensive review for machine learning based human papillomavirus detection in forensic identification with multiple medical samples.
发表日期：2023
作者：
Huanchun Yao, Xinglong Zhang
来源：
Frontiers in Microbiology
摘要：
人乳头瘤病毒（HPV）是通过性传播的病毒。宫颈癌是癌症发病率最高的一种，几乎所有患者都伴随有HPV感染。此外，多种癌症的发生也与HPV感染相关。随着公共健康意识的增强，HPV疫苗在近年来得到广泛应用。在这种情况下，HPV检测不仅需要具有敏感性和特异性，还需要追踪HPV感染的来源。通过机器学习和深度学习，可以更有效地利用医学检查的信息。在本综述中，我们讨论了结合机器学习和深度学习的HPV检测的最新进展。版权所有 © 2023 Yao and Zhang.
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.Copyright © 2023 Yao and Zhang.