通过人工智能和纳米细胞分析技术的进步解决宫颈癌筛查不均衡问题。

IF 2.9 Q2 BIOPHYSICS
Zhenzhong Yang, Jack Francisco, Alexandra S Reese, David R Spriggs, Hyungsoon Im, Cesar M Castro
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引用次数: 0

摘要

几乎所有的宫颈癌病例都是由人类乳头瘤病毒(HPV)引起的。宫颈癌前病变的检测为治愈转移后的致命疾病提供了机会之窗。随着人们对高危 HPV 感染的生物学特性和自然病程有了更深入的了解,筛查方法已从主观的巴氏涂片检查转向更复杂、更客观的策略。这使得以 HPV 为基础的宫颈癌筛查测试的广度和深度大幅增加,尤其是在资源有限的发达国家。许多中低收入国家(LMICs)较难获得先进的实验室和医疗资源,因此开发了新的护理点(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筛查技术和计算策略如何改进传统方法,以及这些技术和策略实现的前景如何进一步使宫颈癌筛查民主化并促进疾病预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Addressing cervical cancer screening disparities through advances in artificial intelligence and nanotechnologies for cellular profiling.

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.

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