• 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

Barriers to Extracting and Harmonizing Glaucoma Testing Data: Gaps, Shortcomings, and the Pursuit of FAIRness.

作者信息

Radgoudarzi Niloofar, Hallaj Shahin, Boland Michael V, Stagg Brian, Wang Sophia Y, Xu Benjamin, Swaminathan Swarup S, Brown Eric N, Chen Aiyin, Sun Catherine Q, Amarasekera Dilru C, Myers Jonathan S, Saifee Murtaza, Halfpenny William, Dirkes Keri, Zangwill Linda, Goetz Kerry E, Hribar Michelle, Baxter Sally L

机构信息

La Jolla, California.

Boston, Massachusetts.

出版信息

Ophthalmol Sci. 2024 Sep 14;4(6):100621. doi: 10.1016/j.xops.2024.100621. eCollection 2024 Nov-Dec.

DOI:10.1016/j.xops.2024.100621
PMID:39429240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11490894/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ce/11490894/dc343d819920/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ce/11490894/dc343d819920/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ce/11490894/dc343d819920/gr1.jpg

相似文献

1
Barriers to Extracting and Harmonizing Glaucoma Testing Data: Gaps, Shortcomings, and the Pursuit of FAIRness.提取和统一青光眼检测数据的障碍:差距、不足与对公平性的追求
Ophthalmol Sci. 2024 Sep 14;4(6):100621. doi: 10.1016/j.xops.2024.100621. eCollection 2024 Nov-Dec.
2
Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.哈佛青光眼公平性:用于公平学习和公平身份归一化的视网膜神经疾病数据集。
IEEE Trans Med Imaging. 2024 Jul;43(7):2623-2633. doi: 10.1109/TMI.2024.3377552. Epub 2024 Jul 1.
3
The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models.种族、族裔和性别对青光眼预测模型人工智能公平性的影响
Ophthalmol Sci. 2024 Aug 14;5(1):100596. doi: 10.1016/j.xops.2024.100596. eCollection 2025 Jan-Feb.
4
Punishing the lemon: the ethics of actuarial fairness.惩罚柠檬:精算公平的伦理。
J Am Coll Radiol. 2012 Dec;9(12):887-93. doi: 10.1016/j.jacr.2012.09.012.
5
Prior information and oculomotor initiation: the effect of cues in gaps.先前信息与动眼神经启动:间隙中线索的影响
Exp Brain Res. 2009 Jan;192(1):75-85. doi: 10.1007/s00221-008-1556-9. Epub 2008 Sep 2.
6
Trends and considerations in the pursuit of postgraduate training: Motivations, barriers, and well-being.追求研究生培训的趋势与考量:动机、障碍与幸福感
Am J Health Syst Pharm. 2025 Jan 4. doi: 10.1093/ajhp/zxae368.
7
Algorithmic Individual Fairness and Healthcare: A Scoping Review.算法个体公平性与医疗保健:一项范围综述
medRxiv. 2024 Mar 26:2024.03.25.24304853. doi: 10.1101/2024.03.25.24304853.
8
Perceived fairness of direct-to-consumer genetic testing business models.对消费者直接基因检测商业模式的感知公平性。
Electron Mark. 2022;32(3):1621-1638. doi: 10.1007/s12525-022-00571-x. Epub 2022 Jul 18.
9
Deep Learning-Based Glaucoma Detection Using Clinical Notes: A Comparative Study of Long Short-Term Memory and Convolutional Neural Network Models.基于深度学习的青光眼检测:长短期记忆模型与卷积神经网络模型的比较研究
Diagnostics (Basel). 2025 Mar 22;15(7):807. doi: 10.3390/diagnostics15070807.
10
Algorithmic individual fairness and healthcare: a scoping review.算法个体公平性与医疗保健:一项范围综述
JAMIA Open. 2024 Dec 30;8(1):ooae149. doi: 10.1093/jamiaopen/ooae149. eCollection 2025 Feb.

引用本文的文献

1
A Practical Guide to Evaluating Artificial Intelligence Imaging Models in Scientific Literature.科学文献中人工智能成像模型评估实用指南。
Ophthalmol Sci. 2025 Jun 9;5(6):100847. doi: 10.1016/j.xops.2025.100847. eCollection 2025 Nov-Dec.
2
The march to harmonized imaging standards for retinal imaging.迈向视网膜成像统一标准的征程。
Prog Retin Eye Res. 2025 Jul;107:101363. doi: 10.1016/j.preteyeres.2025.101363. Epub 2025 May 11.

本文引用的文献

1
Proactive Decision Support for Glaucoma Treatment: Predicting Surgical Interventions with Clinically Available Data.青光眼治疗的主动决策支持:利用临床可用数据预测手术干预
Bioengineering (Basel). 2024 Jan 30;11(2):140. doi: 10.3390/bioengineering11020140.
2
Artificial intelligence in glaucoma: opportunities, challenges, and future directions.人工智能在青光眼领域的应用:机遇、挑战与未来方向。
Biomed Eng Online. 2023 Dec 16;22(1):126. doi: 10.1186/s12938-023-01187-8.
3
Advancing Toward a Common Data Model in Ophthalmology: Gap Analysis of General Eye Examination Concepts to Standard Observational Medical Outcomes Partnership (OMOP) Concepts.
迈向眼科通用数据模型:普通眼科检查概念与标准观察性医学结局合作组织(OMOP)概念的差距分析
Ophthalmol Sci. 2023 Aug 25;3(4):100391. doi: 10.1016/j.xops.2023.100391. eCollection 2023 Dec.
4
Accelerating Care: A Roadmap to Interoperable Ophthalmic Imaging Standards in the United States.加速医疗:美国眼科成像互操作性标准路线图。
Ophthalmology. 2024 Jan;131(1):12-15. doi: 10.1016/j.ophtha.2023.10.001. Epub 2023 Nov 18.
5
Thirty Years of the DICOM Standard.DICOM 标准三十年。
Tomography. 2023 Oct 6;9(5):1829-1838. doi: 10.3390/tomography9050145.
6
Glaucoma: now and beyond.青光眼:现在与未来。
Lancet. 2023 Nov 11;402(10414):1788-1801. doi: 10.1016/S0140-6736(23)01289-8. Epub 2023 Sep 21.
7
Big Data and Artificial Intelligence in Ophthalmology: Where Are We Now?眼科领域的大数据与人工智能:我们目前的进展如何?
Ophthalmol Sci. 2021 Jun 25;1(2):100036. doi: 10.1016/j.xops.2021.100036. eCollection 2021 Jun.
8
The American Academy of Ophthalmology IRIS Registry (Intelligent Research In Sight): current and future state of big data analytics.美国眼科学会虹膜注册中心(智能研究在视野中):大数据分析的现状和未来。
Curr Opin Ophthalmol. 2022 Sep 1;33(5):394-398. doi: 10.1097/ICU.0000000000000869.
9
Prevalence of primary open angle glaucoma in the last 20 years: a meta-analysis and systematic review.过去 20 年原发性开角型青光眼的患病率:一项荟萃分析和系统评价。
Sci Rep. 2021 Jul 2;11(1):13762. doi: 10.1038/s41598-021-92971-w.
10
Glaucoma.青光眼。
Med Clin North Am. 2021 May;105(3):493-510. doi: 10.1016/j.mcna.2021.01.004. Epub 2021 Apr 2.