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基于机器学习的多医学样本法医鉴定中人类乳头瘤病毒检测的综合综述。

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

作者信息

Yao Huanchun, Zhang Xinglong

机构信息

Department of Cancer, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.

Department of Hematology, The Fourth Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.

出版信息

Front Microbiol. 2023 Jul 17;14:1232295. doi: 10.3389/fmicb.2023.1232295. eCollection 2023.

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.

摘要

人乳头瘤病毒(HPV)是一种性传播病毒。宫颈癌是发病率最高的癌症之一,几乎所有患者都伴有HPV感染。此外,多种癌症的发生也与HPV感染有关。近年来,随着公众健康意识的提高,HPV疫苗接种已广泛普及。在这种背景下,HPV检测不仅需要具备敏感性和特异性,还需要追踪HPV感染源。通过机器学习和深度学习,可以更有效地利用医学检查信息。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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4c4/10387549/0bc18e3a9c06/fmicb-14-1232295-g001.jpg

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