Anticipating artificial intelligence in mammography screening: views of Swedish breast radiologists.

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES BMJ Health & Care Informatics Pub Date : 2023-05-01 DOI:10.1136/bmjhci-2022-100712
Charlotte Högberg, Stefan Larsson, Kristina Lång
{"title":"Anticipating artificial intelligence in mammography screening: views of Swedish breast radiologists.","authors":"Charlotte Högberg, Stefan Larsson, Kristina Lång","doi":"10.1136/bmjhci-2022-100712","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Artificial intelligence (AI) is increasingly tested and integrated into breast cancer screening. Still, there are unresolved issues regarding its possible ethical, social and legal impacts. Furthermore, the perspectives of different actors are lacking. This study investigates the views of breast radiologists on AI-supported mammography screening, with a focus on attitudes, perceived benefits and risks, accountability of AI use, and potential impact on the profession.</p><p><strong>Methods: </strong>We conducted an online survey of Swedish breast radiologists. As early adopter of breast cancer screening, and digital technologies, Sweden is a particularly interesting case to study. The survey had different themes, including: attitudes and responsibilities pertaining to AI, and AI's impact on the profession. Responses were analysed using descriptive statistics and correlation analyses. Free texts and comments were analysed using an inductive approach.</p><p><strong>Results: </strong>Overall, respondents (47/105, response rate 44.8%) were highly experienced in breast imaging and had a mixed knowledge of AI. A majority (n=38, 80.8%) were positive/somewhat positive towards integrating AI in mammography screening. Still, many considered there to be potential risks to a high/somewhat high degree (n=16, 34.1%) or were uncertain (n=16, 34.0%). Several important uncertainties were identified, such as defining liable actor(s) when AI is integrated into medical decision-making.</p><p><strong>Conclusions: </strong>Swedish breast radiologists are largely positive towards integrating AI in mammography screening, but there are significant uncertainties that need to be addressed, especially regarding risks and responsibilities. The results stress the importance of understanding actor-specific and context-specific challenges to responsible implementation of AI in healthcare.</p>","PeriodicalId":9050,"journal":{"name":"BMJ Health & Care Informatics","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230899/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Health & Care Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjhci-2022-100712","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives: Artificial intelligence (AI) is increasingly tested and integrated into breast cancer screening. Still, there are unresolved issues regarding its possible ethical, social and legal impacts. Furthermore, the perspectives of different actors are lacking. This study investigates the views of breast radiologists on AI-supported mammography screening, with a focus on attitudes, perceived benefits and risks, accountability of AI use, and potential impact on the profession.

Methods: We conducted an online survey of Swedish breast radiologists. As early adopter of breast cancer screening, and digital technologies, Sweden is a particularly interesting case to study. The survey had different themes, including: attitudes and responsibilities pertaining to AI, and AI's impact on the profession. Responses were analysed using descriptive statistics and correlation analyses. Free texts and comments were analysed using an inductive approach.

Results: Overall, respondents (47/105, response rate 44.8%) were highly experienced in breast imaging and had a mixed knowledge of AI. A majority (n=38, 80.8%) were positive/somewhat positive towards integrating AI in mammography screening. Still, many considered there to be potential risks to a high/somewhat high degree (n=16, 34.1%) or were uncertain (n=16, 34.0%). Several important uncertainties were identified, such as defining liable actor(s) when AI is integrated into medical decision-making.

Conclusions: Swedish breast radiologists are largely positive towards integrating AI in mammography screening, but there are significant uncertainties that need to be addressed, especially regarding risks and responsibilities. The results stress the importance of understanding actor-specific and context-specific challenges to responsible implementation of AI in healthcare.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
乳房 X 射线摄影筛查中的人工智能预测:瑞典乳腺放射科医生的观点。
目的:人工智能(AI)越来越多地应用于乳腺癌筛查。然而,有关其可能产生的伦理、社会和法律影响的问题仍未得到解决。此外,还缺乏不同参与者的观点。本研究调查了乳腺放射科医生对人工智能支持的乳腺X光筛查的看法,重点是态度、感知到的益处和风险、人工智能使用的责任以及对行业的潜在影响:我们对瑞典乳腺放射科医生进行了在线调查。作为乳腺癌筛查和数字技术的早期采用者,瑞典是一个特别值得研究的案例。调查有不同的主题,包括:对人工智能的态度和责任,以及人工智能对该行业的影响。我们使用描述性统计和相关性分析对答复进行了分析。自由文本和评论采用归纳法进行分析:总体而言,受访者(47/105,回复率 44.8%)在乳腺成像方面经验丰富,对人工智能的了解程度参差不齐。大多数受访者(38 人,占 80.8%)对将人工智能纳入乳腺 X 光筛查持积极或略为积极的态度。但也有很多人认为潜在风险很高(16 人,34.1%)或不确定(16 人,34.0%)。研究还发现了一些重要的不确定因素,如在将人工智能纳入医疗决策时如何界定责任主体:结论:瑞典乳腺放射医师对将人工智能纳入乳腺 X 射线筛查持积极态度,但仍有许多不确定因素需要解决,尤其是在风险和责任方面。研究结果强调了了解特定行为者和特定环境对负责任地将人工智能应用于医疗保健的挑战的重要性。
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 去求助
来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
期刊最新文献
Understanding prescribing errors for system optimisation: the technology-related error mechanism classification. Detection of hypertension from pharyngeal images using deep learning algorithm in primary care settings in Japan. PubMed captures more fine-grained bibliographic data on scientific commentary than Web of Science: a comparative analysis. Method to apply temporal graph analysis on electronic patient record data to explore healthcare professional-patient interaction intensity: a cohort study. Harnessing digital footprint data for population health: a discussion on collaboration, challenges and opportunities in the UK.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1