Artificial intelligence and radiotherapy: Evolution or revolution?

IF 1.5 4区 医学 Q4 ONCOLOGY
Charlotte Robert , Philippe Meyer , Brigitte Séroussi , Thomas Leroy , Jean-Emmanuel Bibault
{"title":"Artificial intelligence and radiotherapy: Evolution or revolution?","authors":"Charlotte Robert ,&nbsp;Philippe Meyer ,&nbsp;Brigitte Séroussi ,&nbsp;Thomas Leroy ,&nbsp;Jean-Emmanuel Bibault","doi":"10.1016/j.canrad.2024.09.003","DOIUrl":null,"url":null,"abstract":"<div><div>The integration of artificial intelligence, particularly deep learning algorithms, into radiotherapy represents a transformative shift in the field, enhancing accuracy, efficiency, and personalized care. This paper explores the multifaceted impact of artificial intelligence on radiotherapy, the evolution of the roles of radiation oncologists and medical physicists, and the associated practical challenges. The adoption of artificial intelligence promises to revolutionize the profession by automating repetitive tasks, improving diagnostic precision, and enabling adaptive radiotherapy. However, it also introduces significant risks, such as automation bias, verification failures, and the potential erosion of clinical skills. Ethical considerations, such as maintaining patient autonomy and addressing biases in artificial intelligence systems, are critical to ensuring the responsible use of artificial intelligence. Continuous training and development of robust quality assurance programs are required to mitigate these risks and maximize the benefits of artificial intelligence in radiotherapy.</div></div>","PeriodicalId":9504,"journal":{"name":"Cancer Radiotherapie","volume":"28 6","pages":"Pages 503-509"},"PeriodicalIF":1.5000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Radiotherapie","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1278321824001501","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The integration of artificial intelligence, particularly deep learning algorithms, into radiotherapy represents a transformative shift in the field, enhancing accuracy, efficiency, and personalized care. This paper explores the multifaceted impact of artificial intelligence on radiotherapy, the evolution of the roles of radiation oncologists and medical physicists, and the associated practical challenges. The adoption of artificial intelligence promises to revolutionize the profession by automating repetitive tasks, improving diagnostic precision, and enabling adaptive radiotherapy. However, it also introduces significant risks, such as automation bias, verification failures, and the potential erosion of clinical skills. Ethical considerations, such as maintaining patient autonomy and addressing biases in artificial intelligence systems, are critical to ensuring the responsible use of artificial intelligence. Continuous training and development of robust quality assurance programs are required to mitigate these risks and maximize the benefits of artificial intelligence in radiotherapy.
人工智能与放射治疗:进化还是革命?
将人工智能,特别是深度学习算法,融入放射治疗是该领域的一次变革,可提高准确性、效率和个性化护理。本文探讨了人工智能对放射治疗的多方面影响、放射肿瘤学家和医学物理学家角色的演变以及相关的实际挑战。人工智能的应用有望通过自动化重复性任务、提高诊断精确度和实现自适应放疗来彻底改变这一行业。然而,它也带来了巨大的风险,如自动化偏差、验证失败以及临床技能的潜在削弱。要确保负责任地使用人工智能,道德方面的考虑至关重要,例如维护患者自主权和解决人工智能系统中的偏见问题。要降低这些风险,最大限度地发挥人工智能在放射治疗中的优势,就必须持续开展培训并制定强有力的质量保证计划。
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 Radiotherapie
Cancer Radiotherapie 医学-核医学
CiteScore
2.20
自引率
23.10%
发文量
129
审稿时长
63 days
期刊介绍: Cancer/radiothérapie se veut d''abord et avant tout un organe francophone de publication des travaux de recherche en radiothérapie. La revue a pour objectif de diffuser les informations majeures sur les travaux de recherche en cancérologie et tout ce qui touche de près ou de loin au traitement du cancer par les radiations : technologie, radiophysique, radiobiologie et radiothérapie clinique.
×
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