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通过人工智能和用于细胞分析的纳米技术进展解决宫颈癌筛查差异问题。

Addressing cervical cancer screening disparities through advances in artificial intelligence and nanotechnologies for cellular profiling.

作者信息

Yang Zhenzhong, Francisco Jack, Reese Alexandra S, Spriggs David R, Im Hyungsoon, Castro Cesar M

机构信息

Cancer Center, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

出版信息

Biophys Rev (Melville). 2021 Mar;2(1):011303. doi: 10.1063/5.0043089.

Abstract

Almost all cases of cervical cancer are caused by the human papilloma virus (HPV). Detection of pre-cancerous cervical changes provides a window of opportunity for cure of an otherwise lethal disease when metastatic. With a greater understanding of the biology and natural course of high-risk HPV infections, screening methods have shifted beyond subjective Pap smears toward more sophisticated and objective tactics. This has led to a substantial growth in the breadth and depth of HPV-based cervical cancer screening tests, especially in developed countries without constrained resources. Many low- and middle-income countries (LMICs) have less access to advanced laboratories and healthcare resources, so new point-of-care (POC) technologies have been developed to provide test results in real time, improve the efficiency of techniques, and increase screening adoption. In this Review, we will discuss how novel decentralized screening technologies and computational strategies improve upon traditional methods and how their realized promise could further democratize cervical cancer screening and promote greater disease prevention.

摘要

几乎所有宫颈癌病例都是由人乳头瘤病毒(HPV)引起的。检测宫颈癌前病变为治愈转移性致死性疾病提供了一个机会窗口。随着对高危HPV感染生物学和自然病程的深入了解,筛查方法已从主观的巴氏涂片转向更复杂、客观的策略。这使得基于HPV的宫颈癌筛查测试在广度和深度上大幅增长,尤其是在资源不受限的发达国家。许多低收入和中等收入国家(LMICs)难以获得先进实验室和医疗资源,因此已开发出新的即时检测(POC)技术,以实时提供检测结果,提高技术效率,并增加筛查的采用率。在本综述中,我们将讨论新型分散式筛查技术和计算策略如何改进传统方法,以及它们实现的前景如何进一步使宫颈癌筛查民主化并促进更好的疾病预防。

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