• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

患者对糖尿病眼病筛查人工智能的看法。

Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening.

机构信息

Department of Ophthalmology, Auckland, New Zealand.

Department of Ophthalmology, University of Auckland, Auckland, New Zealand.

出版信息

Asia Pac J Ophthalmol (Phila). 2022 May 1;11(3):287-293. doi: 10.1097/APO.0000000000000525.

DOI:10.1097/APO.0000000000000525
PMID:35772087
Abstract

PURPOSE

Artificial intelligence (AI) technology is poised to revolutionize modern delivery of health care services. We set to evaluate the patient perspective of AI use in diabetic retinal screening.

DESIGN

Survey.

METHODS

Four hundred thirty-eight patients undergoing diabetic retinal screening across New Zealand participated in a survey about their opinion of AI technology in retinal screening. The survey consisted of 13 questions covering topics of awareness, trust, and receptivity toward AI systems.

RESULTS

The mean age was 59 years. The majority of participants identified as New Zealand European (50%), followed by Asian (31%), Pacific Islander (10%), and Maori (5%). Whilst 73% of participants were aware of AI, only 58% have heard of it being implemented in health care. Overall, 78% of respondents were comfortable with AI use in their care, with 53% saying they would trust an AI-assisted screening program as much as a health professional. Despite having a higher awareness of AI, younger participants had lower trust in AI systems. A higher proportion of Maori and Pacific participants indicated a preference toward human-led screening. The main perceived benefits of AI included faster diagnostic speeds and greater accuracy.

CONCLUSIONS

There is low awareness of clinical AI applications among our participants. Despite this, most are receptive toward the implementation of AI in diabetic eye screening. Overall, there was a strong preference toward continual involvement of clinicians in the screening process. There are key recommendations to enhance the receptivity of the public toward incorporation of AI into retinal screening programs.

摘要

目的

人工智能(AI)技术有望彻底改变现代医疗服务的提供方式。我们旨在评估患者对糖尿病视网膜筛查中 AI 使用的看法。

设计

调查。

方法

新西兰各地 438 名接受糖尿病视网膜筛查的患者参与了一项关于他们对视网膜筛查中 AI 技术看法的调查。该调查由 13 个问题组成,涵盖了对 AI 系统的认识、信任和接受度等主题。

结果

平均年龄为 59 岁。大多数参与者为新西兰欧洲人(50%),其次是亚洲人(31%)、太平洋岛民(10%)和毛利人(5%)。尽管 73%的参与者了解 AI,但只有 58%听说过它在医疗保健中的应用。总体而言,78%的受访者对 AI 在其护理中的使用感到满意,其中 53%表示他们会像信任医疗保健专业人员一样信任 AI 辅助筛查计划。尽管对 AI 的认识较高,但年轻参与者对 AI 系统的信任度较低。更多的毛利人和太平洋岛民参与者表示倾向于由人类主导的筛查。AI 的主要预期收益包括更快的诊断速度和更高的准确性。

结论

我们的参与者对临床 AI 应用的认识较低。尽管如此,大多数人还是对在糖尿病眼病筛查中实施 AI 持欢迎态度。总体而言,人们强烈倾向于继续让临床医生参与筛查过程。有一些关键建议可以提高公众对将 AI 纳入视网膜筛查计划的接受程度。

相似文献

1
Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening.患者对糖尿病眼病筛查人工智能的看法。
Asia Pac J Ophthalmol (Phila). 2022 May 1;11(3):287-293. doi: 10.1097/APO.0000000000000525.
2
What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease? Development and validation of a survey for use in a secondary care screening setting.糖尿病患者和国民保健署工作人员对人工智能辅助糖尿病眼病筛查的潜在实施有何看法和顾虑?在二级保健筛查环境中使用的调查工具的开发和验证。
BMJ Open. 2023 Nov 15;13(11):e075558. doi: 10.1136/bmjopen-2023-075558.
3
Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.患者对深度学习辅助糖尿病视网膜病变筛查活动中人工智能的看法:真实世界评估。
J Diabetes Sci Technol. 2024 May;18(3):750-751. doi: 10.1177/19322968241234378. Epub 2024 Feb 25.
4
Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.澳大利亚内分泌科和原住民医疗保健环境中基于真实世界人工智能的糖尿病视网膜病变机会性筛查。
Sci Rep. 2021 Aug 4;11(1):15808. doi: 10.1038/s41598-021-94178-5.
5
Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes.自主即时糖尿病视网膜病变筛查在儿童糖尿病患者中的成本效益分析。
JAMA Ophthalmol. 2020 Oct 1;138(10):1063-1069. doi: 10.1001/jamaophthalmol.2020.3190.
6
The SEE Study: Safety, Efficacy, and Equity of Implementing Autonomous Artificial Intelligence for Diagnosing Diabetic Retinopathy in Youth.SEE 研究:在青少年糖尿病视网膜病变诊断中实施自主人工智能的安全性、有效性和公平性。
Diabetes Care. 2021 Mar;44(3):781-787. doi: 10.2337/dc20-1671. Epub 2021 Jan 21.
7
ARTEFICIAL INTELLIGENCE IN DIABETIC RETINOPATHY SCREENING. A REVIEW.人工智能在糖尿病视网膜病变筛查中的应用。综述。
Cesk Slov Oftalmol. 2021 Fall;77(5):224-231. doi: 10.31348/2021/6.
8
Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.人工智能利用深度学习在非洲筛查可转诊和威胁视力的糖尿病视网膜病变:一项临床验证研究。
Lancet Digit Health. 2019 May;1(1):e35-e44. doi: 10.1016/S2589-7500(19)30004-4. Epub 2019 May 2.
9
Patients' Perceptions Toward Human-Artificial Intelligence Interaction in Health Care: Experimental Study.患者对医疗保健中人机交互的看法:实验研究。
J Med Internet Res. 2021 Nov 25;23(11):e25856. doi: 10.2196/25856.
10
Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data.人工智能在城市中国社区为基础的糖尿病视网膜病变远程医疗筛查中的应用:基于真实世界数据的成本效果和成本效益分析。
JMIR Public Health Surveill. 2023 Feb 23;9:e41624. doi: 10.2196/41624.

引用本文的文献

1
A comparative study of machine learning models for automated detection and classification of retinal diseases in Ghana.加纳用于视网膜疾病自动检测和分类的机器学习模型的比较研究。
PLoS One. 2025 Aug 1;20(8):e0327743. doi: 10.1371/journal.pone.0327743. eCollection 2025.
2
Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients.医院患者对医疗保健和诊断领域人工智能的跨国态度。
JAMA Netw Open. 2025 Jun 2;8(6):e2514452. doi: 10.1001/jamanetworkopen.2025.14452.
3
Indecision on the use of artificial intelligence in healthcare-A qualitative study of patient perspectives on trust, responsibility and self-determination using AI-CDSS.
医疗保健领域人工智能应用的决策困境——一项关于患者对使用人工智能临床决策支持系统的信任、责任和自主决定权观点的定性研究
Digit Health. 2025 May 30;11:20552076251339522. doi: 10.1177/20552076251339522. eCollection 2025 Jan-Dec.
4
Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment.对人工智能在患者医疗保健中应用的态度:来自一项人口调查情景实验的证据。
J Med Internet Res. 2025 May 27;27:e70179. doi: 10.2196/70179.
5
Valuable insights into general practice staff's experiences and perspectives on AI-assisted diabetic retinopathy screening-An interview study.关于全科医疗工作人员对人工智能辅助糖尿病视网膜病变筛查的经验和看法的宝贵见解——一项访谈研究。
Front Med (Lausanne). 2025 Mar 11;12:1565532. doi: 10.3389/fmed.2025.1565532. eCollection 2025.
6
Implementation of A New, Mobile Diabetic Retinopathy Screening Model Incorporating Artificial Intelligence in Remote Western Australia.在西澳大利亚偏远地区实施一种结合人工智能的新型移动糖尿病视网膜病变筛查模式。
Aust J Rural Health. 2025 Apr;33(2):e70031. doi: 10.1111/ajr.70031.
7
Awareness, Knowledge, Attitudes, and Practices Regarding Diabetic Retinopathy Among Residents of Jazan City, Saudi Arabia.沙特阿拉伯吉赞市居民对糖尿病视网膜病变的认知、知识、态度及行为
Cureus. 2024 Oct 10;16(10):e71219. doi: 10.7759/cureus.71219. eCollection 2024 Oct.
8
Perceptions Toward Using Artificial Intelligence and Technology for Asthma Attack Risk Prediction: Qualitative Exploration of Māori Views.对使用人工智能和技术进行哮喘发作风险预测的看法:毛利人观点的定性探讨。
JMIR Form Res. 2024 Oct 30;8:e59811. doi: 10.2196/59811.
9
Implementation of Artificial Intelligence-Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study.魁北克一家三级护理医院中基于人工智能的糖尿病视网膜病变筛查的实施:前瞻性验证研究
JMIR Diabetes. 2024 Sep 3;9:e59867. doi: 10.2196/59867.
10
Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.患者对深度学习辅助糖尿病视网膜病变筛查活动中人工智能的看法:真实世界评估。
J Diabetes Sci Technol. 2024 May;18(3):750-751. doi: 10.1177/19322968241234378. Epub 2024 Feb 25.