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通过人工智能开展乳腺癌组织筛查项目的未来:一项范围综述

The Future of Breast Cancer Organized Screening Program Through Artificial Intelligence: A Scoping Review.

作者信息

Altobelli Emma, Angeletti Paolo Matteo, Ciancaglini Marco, Petrocelli Reimondo

机构信息

Department of Life, Health and Environmental Sciences, Section of Epidemiology and Biostatistics Unit, University of L'Aquila, 67100 L'Aquila, Italy.

Cardiovascular Department, UO of Cardiac Anesthesia of the IRCCS Humanitas Research Hospital, 20089 Rozzano, Italy.

出版信息

Healthcare (Basel). 2025 Feb 10;13(4):378. doi: 10.3390/healthcare13040378.

Abstract

: The aim of this scoping review was to evaluate whether artificial intelligence integrated into breast cancer screening work strategies could help resolve some diagnostic issues that still remain. : PubMed, Web of Science, and Scopus were consulted. The literature research was updated to 28 May 2024. The PRISMA method of selecting articles was used. The articles were classified according to the type of publication (meta-analysis, trial, prospective, and retrospective studies); moreover, retrospective studies were based on citizen recruitment (organized screening vs. spontaneous screening and a combination of both). : Meta-analyses showed that AI had an effective reduction in the radiologists' reading time of radiological images, with a variation from 17 to 91%. Furthermore, they highlighted how the use of artificial intelligence software improved the diagnostic accuracy. Systematic review speculated that AI could reduce false negatives and positives and detect subtle abnormalities missed by human observers. DR with AI results from organized screening showed a higher recall rate, specificity, and PPV. Data from opportunistic screening found that AI could reduce interval cancer with a corresponding reduction in serious outcome. Nevertheless, the analysis of this review suggests that the study of breast density and interval cancer still requires numerous applications. : Artificial intelligence appears to be a promising technology for health, with consequences that can have a major impact on healthcare systems. Where screening is opportunistic and involves only one human reader, the use of AI can increase diagnostic performance enough to equal that of double human reading.

摘要

本综述的目的是评估整合到乳腺癌筛查工作策略中的人工智能是否有助于解决一些仍然存在的诊断问题。查阅了PubMed、科学网和Scopus。文献研究更新至2024年5月28日。采用PRISMA文章选择方法。文章根据出版物类型(荟萃分析、试验、前瞻性和回顾性研究)进行分类;此外,回顾性研究基于公民招募情况(有组织的筛查与自发筛查以及两者的结合)。荟萃分析表明,人工智能有效地减少了放射科医生阅读放射图像的时间,减少幅度从17%到91%不等。此外,它们还强调了人工智能软件的使用如何提高了诊断准确性。系统评价推测,人工智能可以减少假阴性和假阳性,并检测出人类观察者遗漏的细微异常。有组织筛查的人工智能辅助数字乳腺断层合成(DR)结果显示召回率、特异性和阳性预测值更高。机会性筛查的数据发现,人工智能可以减少间期癌,并相应降低严重后果的发生率。然而,本综述的分析表明,乳腺密度和间期癌的研究仍需要大量应用。人工智能似乎是一项有前景的健康技术,其影响可能对医疗系统产生重大影响。在机会性筛查且仅涉及一名人类阅片者的情况下,使用人工智能可以将诊断性能提高到与双人阅片相当的水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac9f/11855082/847402e57841/healthcare-13-00378-g001.jpg

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