Artificial intelligence strengthenes cervical cancer screening - present and future.

IF 5.6 2区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Tong Wu, Eric Lucas, Fanghui Zhao, Partha Basu, Youlin Qiao
{"title":"Artificial intelligence strengthenes cervical cancer screening - present and future.","authors":"Tong Wu, Eric Lucas, Fanghui Zhao, Partha Basu, Youlin Qiao","doi":"10.20892/j.issn.2095-3941.2024.0198","DOIUrl":null,"url":null,"abstract":"<p><p>Cervical cancer is a severe threat to women's health. The majority of cervical cancer cases occur in developing countries. The WHO has proposed screening 70% of women with high-performance tests between 35 and 45 years of age by 2030 to accelerate the elimination of cervical cancer. Due to an inadequate health infrastructure and organized screening strategy, most low- and middle-income countries are still far from achieving this goal. As part of the efforts to increase performance of cervical cancer screening, it is necessary to investigate the most accurate, efficient, and effective methods and strategies. Artificial intelligence (AI) is rapidly expanding its application in cancer screening and diagnosis and deep learning algorithms have offered human-like interpretation capabilities on various medical images. AI will soon have a more significant role in improving the implementation of cervical cancer screening, management, and follow-up. This review aims to report the state of AI with respect to cervical cancer screening. We discuss the primary AI applications and development of AI technology for image recognition applied to detection of abnormal cytology and cervical neoplastic diseases, as well as the challenges that we anticipate in the future.</p>","PeriodicalId":9611,"journal":{"name":"Cancer Biology & Medicine","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11523278/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Biology & Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.20892/j.issn.2095-3941.2024.0198","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Cervical cancer is a severe threat to women's health. The majority of cervical cancer cases occur in developing countries. The WHO has proposed screening 70% of women with high-performance tests between 35 and 45 years of age by 2030 to accelerate the elimination of cervical cancer. Due to an inadequate health infrastructure and organized screening strategy, most low- and middle-income countries are still far from achieving this goal. As part of the efforts to increase performance of cervical cancer screening, it is necessary to investigate the most accurate, efficient, and effective methods and strategies. Artificial intelligence (AI) is rapidly expanding its application in cancer screening and diagnosis and deep learning algorithms have offered human-like interpretation capabilities on various medical images. AI will soon have a more significant role in improving the implementation of cervical cancer screening, management, and follow-up. This review aims to report the state of AI with respect to cervical cancer screening. We discuss the primary AI applications and development of AI technology for image recognition applied to detection of abnormal cytology and cervical neoplastic diseases, as well as the challenges that we anticipate in the future.

人工智能加强宫颈癌筛查--现在与未来。
宫颈癌严重威胁妇女的健康。大多数宫颈癌病例发生在发展中国家。世卫组织提出,到 2030 年,用高性能检测对 70%的 35 至 45 岁妇女进行筛查,以加速消除宫颈癌。由于卫生基础设施和有组织的筛查策略不足,大多数中低收入国家距离实现这一目标还很遥远。作为提高宫颈癌筛查绩效工作的一部分,有必要研究最准确、最高效、最有效的方法和策略。人工智能(AI)正在迅速扩大其在癌症筛查和诊断中的应用,深度学习算法为各种医学影像提供了类人解读能力。人工智能将很快在改善宫颈癌筛查、管理和随访的实施方面发挥更重要的作用。本综述旨在报告人工智能在宫颈癌筛查方面的发展状况。我们将讨论应用于异常细胞学和宫颈肿瘤疾病检测的人工智能图像识别技术的主要应用和发展,以及我们预计的未来挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Cancer Biology & Medicine
Cancer Biology & Medicine Medicine-Oncology
CiteScore
9.80
自引率
3.60%
发文量
1143
审稿时长
12 weeks
期刊介绍: Cancer Biology & Medicine (ISSN 2095-3941) is a peer-reviewed open-access journal of Chinese Anti-cancer Association (CACA), which is the leading professional society of oncology in China. The journal quarterly provides innovative and significant information on biological basis of cancer, cancer microenvironment, translational cancer research, and all aspects of clinical cancer research. The journal also publishes significant perspectives on indigenous cancer types in China.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信