A Narrative Review of Ethical Issues in the Use of Artificial Intelligence Enabled Diagnostics for Diabetic Retinopathy.

IF 2.1 4区 医学 Q3 HEALTH CARE SCIENCES & SERVICES
Alexandra Crew, Claire Reidy, Helene-Mari van der Westhuizen, Mackenzie Graham
{"title":"A Narrative Review of Ethical Issues in the Use of Artificial Intelligence Enabled Diagnostics for Diabetic Retinopathy.","authors":"Alexandra Crew, Claire Reidy, Helene-Mari van der Westhuizen, Mackenzie Graham","doi":"10.1111/jep.14237","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Diabetic retinopathy is one of the leading causes of avoidable blindness among adults globally, and screening programmes can enable early diagnosis and prevention of progression. Artificial intelligence (AI) diagnostic solutions have been developed to diagnose diabetic retinopathy. The aim of this review is to identify ethical concerns related to AI-enabled diabetic retinopathy diagnostics and enable future research to explore these issues further.</p><p><strong>Methods: </strong>This is a narrative review that uses thematic analysis methods to develop key findings. We searched two databases, PubMed and Scopus, for papers focused on the intersection of AI, diagnostics, ethics, and diabetic retinopathy and conducted a citation search. Primary research articles published in English between 1 January 2013 and 14 June 2024 were included. From the 1878 papers that were screened, nine papers met inclusion and exclusion criteria and were selected for analysis.</p><p><strong>Results: </strong>We found that existing literature highlights ensuring patient data has appropriate protection and ownership, that bias in algorithm training data is minimised, informed patient decision-making is encouraged, and negative consequences in the context of clinical practice are mitigated.</p><p><strong>Conclusions: </strong>While the technical developments in AI-enabled diabetic retinopathy diagnostics receive the bulk of the research focus, we found that insufficient attention is paid to how this technology is accessed equitably in different settings and which safeguards are needed against exploitative practices. Such ethical issues merit additional exploration and practical problem-solving through primary research. AI-enabled diabetic retinopathy screening has the potential to enable screening at a scale that was previously not possible and could contribute to reducing preventable blindness. It will only achieve this if ethical issues are emphasised, understood, and addressed throughout the translation of this technology to clinical practice.</p>","PeriodicalId":15997,"journal":{"name":"Journal of evaluation in clinical practice","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of evaluation in clinical practice","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/jep.14237","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Diabetic retinopathy is one of the leading causes of avoidable blindness among adults globally, and screening programmes can enable early diagnosis and prevention of progression. Artificial intelligence (AI) diagnostic solutions have been developed to diagnose diabetic retinopathy. The aim of this review is to identify ethical concerns related to AI-enabled diabetic retinopathy diagnostics and enable future research to explore these issues further.

Methods: This is a narrative review that uses thematic analysis methods to develop key findings. We searched two databases, PubMed and Scopus, for papers focused on the intersection of AI, diagnostics, ethics, and diabetic retinopathy and conducted a citation search. Primary research articles published in English between 1 January 2013 and 14 June 2024 were included. From the 1878 papers that were screened, nine papers met inclusion and exclusion criteria and were selected for analysis.

Results: We found that existing literature highlights ensuring patient data has appropriate protection and ownership, that bias in algorithm training data is minimised, informed patient decision-making is encouraged, and negative consequences in the context of clinical practice are mitigated.

Conclusions: While the technical developments in AI-enabled diabetic retinopathy diagnostics receive the bulk of the research focus, we found that insufficient attention is paid to how this technology is accessed equitably in different settings and which safeguards are needed against exploitative practices. Such ethical issues merit additional exploration and practical problem-solving through primary research. AI-enabled diabetic retinopathy screening has the potential to enable screening at a scale that was previously not possible and could contribute to reducing preventable blindness. It will only achieve this if ethical issues are emphasised, understood, and addressed throughout the translation of this technology to clinical practice.

人工智能诊断糖尿病视网膜病变的伦理问题综述》。
导言:糖尿病视网膜病变是导致全球成年人可避免失明的主要原因之一,筛查计划可实现早期诊断并防止病情恶化。目前已开发出人工智能(AI)诊断解决方案来诊断糖尿病视网膜病变。本综述旨在确定与人工智能糖尿病视网膜病变诊断相关的伦理问题,并使未来的研究能够进一步探讨这些问题:这是一篇叙事性综述,采用专题分析方法得出主要结论。我们在 PubMed 和 Scopus 这两个数据库中检索了有关人工智能、诊断、伦理和糖尿病视网膜病变交叉领域的论文,并进行了引文检索。收录了 2013 年 1 月 1 日至 2024 年 6 月 14 日期间发表的英文初级研究文章。从筛选出的 1878 篇论文中,有 9 篇符合纳入和排除标准,并被选中进行分析:我们发现,现有文献强调要确保患者数据得到适当的保护和所有权,最大限度地减少算法训练数据中的偏差,鼓励患者做出知情决策,并减轻临床实践中的负面影响:虽然人工智能糖尿病视网膜病变诊断的技术发展得到了大部分研究的关注,但我们发现,对于如何在不同环境下公平地使用这项技术,以及需要采取哪些保障措施来防止剥削性做法,却没有给予足够的重视。这些伦理问题值得进一步探讨,并通过初级研究解决实际问题。人工智能支持的糖尿病视网膜病变筛查有可能实现以前不可能实现的大规模筛查,并有助于减少可预防的失明。只有在将这项技术转化为临床实践的整个过程中强调、理解和解决伦理问题,才能实现这一目标。
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
CiteScore
4.80
自引率
4.20%
发文量
143
审稿时长
3-8 weeks
期刊介绍: The Journal of Evaluation in Clinical Practice aims to promote the evaluation and development of clinical practice across medicine, nursing and the allied health professions. All aspects of health services research and public health policy analysis and debate are of interest to the Journal whether studied from a population-based or individual patient-centred perspective. Of particular interest to the Journal are submissions on all aspects of clinical effectiveness and efficiency including evidence-based medicine, clinical practice guidelines, clinical decision making, clinical services organisation, implementation and delivery, health economic evaluation, health process and outcome measurement and new or improved methods (conceptual and statistical) for systematic inquiry into clinical practice. Papers may take a classical quantitative or qualitative approach to investigation (or may utilise both techniques) or may take the form of learned essays, structured/systematic reviews and critiques.
×
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