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Global disparity bias in ophthalmology artificial intelligence applications.眼科人工智能应用中的全球差异偏差
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[The development of ophthalmology in artificial intelligence era].[人工智能时代眼科医学的发展]
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1
Generalisability through local validation: overcoming barriers due to data disparity in healthcare.通过局部验证实现可推广性：克服医疗保健中因数据差异导致的障碍。
BMC Ophthalmol. 2021 May 21;21(1):228. doi: 10.1186/s12886-021-01992-6.
2
Predicting sex from retinal fundus photographs using automated deep learning.利用自动化深度学习从眼底照片预测性别。
Sci Rep. 2021 May 13;11(1):10286. doi: 10.1038/s41598-021-89743-x.
3
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.眼科成像公共可用数据集的全球回顾：获取、可用性和可推广性的障碍。
Lancet Digit Health. 2021 Jan;3(1):e51-e66. doi: 10.1016/S2589-7500(20)30240-5. Epub 2020 Oct 1.
4
Multicenter, Head-to-Head, Real-World Validation Study of Seven Automated Artificial Intelligence Diabetic Retinopathy Screening Systems.多中心、头对头、真实世界验证研究七种自动人工智能糖尿病视网膜病变筛查系统。
Diabetes Care. 2021 May;44(5):1168-1175. doi: 10.2337/dc20-1877. Epub 2021 Jan 5.
5
Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening.人工智能在糖尿病视网膜病变筛查中的应用的健康经济和安全考虑。
Transl Vis Sci Technol. 2020 Apr 13;9(2):22. doi: 10.1167/tvst.9.2.22. eCollection 2020 Apr.
6
Accelerating ophthalmic artificial intelligence research: the role of an open access data repository.加速眼科人工智能研究：开放获取数据存储库的作用。
Curr Opin Ophthalmol. 2020 Sep;31(5):337-350. doi: 10.1097/ICU.0000000000000678.
7
Deployment of Artificial Intelligence in Real-World Practice: Opportunity and Challenge.人工智能在实际应用中的部署：机遇与挑战。
Asia Pac J Ophthalmol (Phila). 2020 Jul-Aug;9(4):299-307. doi: 10.1097/APO.0000000000000301.
8
Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.在基层医疗诊所中用于检测糖尿病视网膜病变的基于人工智能的自主诊断系统的关键试验。
NPJ Digit Med. 2018 Aug 28;1:39. doi: 10.1038/s41746-018-0040-6. eCollection 2018.
9
Estimated number of ophthalmologists worldwide (International Council of Ophthalmology update): will we meet the needs?全球眼科医生数量估计（国际眼科理事会更新）：我们能否满足需求？
Br J Ophthalmol. 2020 Apr;104(4):588-592. doi: 10.1136/bjophthalmol-2019-314336. Epub 2019 Jul 2.
10
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.基于深度学习的眼底图像心血管风险因素预测。
Nat Biomed Eng. 2018 Mar;2(3):158-164. doi: 10.1038/s41551-018-0195-0. Epub 2018 Feb 19.

Global disparity bias in ophthalmology artificial intelligence applications.

作者信息

Nakayama Luis Filipe, Kras Ashley, Ribeiro Lucas Zago, Malerbi Fernando Korn, Mendonça Luis Salles, Celi Leo Anthony, Regatieri Caio Vinicius Saito, Waheed Nadia K

机构信息

São Paulo Federal University, São Paulo, SP, Brazil

Retinal Imaging Lab, Harvard University, Cambridge, Massachusetts, USA.

出版信息

BMJ Health Care Inform. 2022 Apr;29(1). doi: 10.1136/bmjhci-2021-100470.

DOI:10.1136/bmjhci-2021-100470
PMID:35396248
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8996038/
Abstract
摘要