人工智能对肺癌筛查的未来影响:系统综述。

BJR open Pub Date : 2024-10-15 eCollection Date: 2024-01-01 DOI:10.1093/bjro/tzae035
Joseph Quirk, Conor Mac Donnchadha, Jonathan Vaantaja, Cameron Mitchell, Nicolas Marchi, Jasmine AlSaleh, Bryan Dalton
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引用次数: 0

摘要

研究目的本研究旨在系统回顾文献,评估基于人工智能的干预措施在肺癌筛查中的应用及其未来影响:采用 PRISMA 准则在三个数据库中筛选相关的已发表文献:方法:采用 PRISMA 准则在三个数据库中筛选相关的已发表文献:PubMed、Scopus 和 Web of Science。文章筛选的搜索关键词包括 "人工智能"、"放射学"、"肺癌"、"筛查 "和 "诊断"。纳入的研究对人工智能在肺癌筛查和诊断中的应用进行了评估:结果:12 项研究符合纳入标准。所有研究都涉及人工智能在肺癌筛查和诊断中的作用。人工智能在以下四个领域表现出良好的能力:(1) 检测,(2) 定性和分化,(3) 辅助人类放射医师的工作,(4) LUNG-RADS 框架的人工智能实施及其辅助该框架的能力。所有研究都报告了积极的结果,在某些情况下,人工智能执行这些任务的能力已接近人类放射科医生的水平:本综述中的人工智能系统被认为是有效的肺癌筛查工具。这些发现对未来在肺癌筛查计划中使用人工智能具有重要意义,因为人工智能可能会被用作肺癌筛查的辅助工具,帮助进行早期准确诊断:基于人工智能的系统似乎是可以协助放射科医生进行肺癌筛查和诊断的强大工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Future implications of artificial intelligence in lung cancer screening: a systematic review.

Objectives: The aim of this study was to systematically review the literature to assess the application of AI-based interventions in lung cancer screening, and its future implications.

Methods: Relevant published literature was screened using PRISMA guidelines across three databases: PubMed, Scopus, and Web of Science. Search terms for article selection included "artificial intelligence," "radiology," "lung cancer," "screening," and "diagnostic." Included studies evaluated the use of AI in lung cancer screening and diagnosis.

Results: Twelve studies met the inclusion criteria. All studies concerned the role of AI in lung cancer screening and diagnosis. The AIs demonstrated promising ability across four domains: (1) detection, (2) characterization and differentiation, (3) augmentation of the work of human radiologists, (4) AI implementation of the LUNG-RADS framework and its ability to augment this framework. All studies reported positive results, demonstrating in some cases AI's ability to perform these tasks to a level close to that of human radiologists.

Conclusions: The AI systems included in this review were found to be effective screening tools for lung cancer. These findings hold important implications for the future use of AI in lung cancer screening programmes as they may see use as an adjunctive tool for lung cancer screening that would aid in making early and accurate diagnosis.

Advances in knowledge: AI-based systems appear to be powerful tools that can assist radiologists with lung cancer screening and diagnosis.

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