Big data and ophthalmic research

被引：36

作者：

Clark, Antony ^{[1
,2
]}

Ng, Jonathon Q. ^{[1
,2
]}

Monet, Nigel ^{[1
,2
]}

Semmens, James B. ^{[1
,2
]}

机构：

[1] Curtin Univ, Fac Hlth Sci, Ctr Populat Hlth Res, Bentley, WA, Australia

[2] Eye & Vis Epidemiol Res EVER Grp, Perth, WA, Australia

来源：

SURVEY OF OPHTHALMOLOGY | 2016年 / 61卷 / 04期

关键词：

data linkage; clinical registry; health services research; ophthalmic epidemiology; big data; OPEN-ANGLE GLAUCOMA; ELECTRONIC MULTICENTER AUDIT; 55; 567; OPERATIONS; NATIONAL CATARACT REGISTER; HOSPITAL DISCHARGE REGISTRY; ISCHEMIC OPTIC NEUROPATHY; IMPAIRED VISUAL FUNCTION; GROWTH-FACTOR INHIBITORS; DIABETIC MACULAR EDEMA; RETINAL VEIN OCCLUSION;

D O I：

10.1016/j.survophthal.2016.01.003

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

Large population-based health administrative databases, clinical registries, and data linkage systems are a rapidly expanding resource for health research. Ophthalmic research has benefited from the use of these databases in expanding the breadth of knowledge in areas such as disease surveillance, disease etiology, health services utilization, and health outcomes. Furthermore, the quantity of data available for research has increased exponentially in recent times, particularly as e-health initiatives come online in health systems across the globe. We review some big data concepts, the databases and data linkage systems used in eye research including their advantages and limitations, the types of studies previously undertaken, and the future direction for big data in eye research. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：443 / 465

页数：23

共 50 条

[1] Big data in ophthalmology: a systematic review of public databases for ophthalmic research
Lin, John C.
Ghauri, Sophia Y.
Lee, Matthew J.
Scott, Ingrid U.
Greenberg, Paul B.
[J]. EYE, 2023, 37 (14) : 3044 - 3046
[2] Big data in ophthalmology: a systematic review of public databases for ophthalmic research
John C. Lin
Sophia Y. Ghauri
Matthew J. Lee
Ingrid U. Scott
Paul B. Greenberg
[J]. Eye, 2023, 37 : 3044 - 3046
[3] Big Data and IS Research
Goes, Paulo B.
[J]. MIS QUARTERLY, 2014, 38 (03) : III - VIII
[4] Research on Big Data and Data Acquisition
Huang, Ning
[J]. PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY (ICMMCT 2017), 2017, 126 : 1268 - 1272
[5] Big Data and Collaboration Research Creating Real Big Data
Zhu, Haibin
[J]. IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE, 2018, 4 (01): : 16 - 19
[6] Big Challenge in Big Data Research: Continual Dispute on Big Data Analysis
Lee, Hae Young
[J]. KOREAN CIRCULATION JOURNAL, 2020, 50 (01) : 69 - 71
[7] Research of Big data and data security
Ren, Qiong
Xu, Zhongyuan
[J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON MATERIALS ENGINEERING AND INFORMATION TECHNOLOGY APPLICATIONS, 2015, 28 : 871 - 875
[8] On the Research of Data Warehouse in Big Data
Qin, Hai-fei
Qian, Zhi-ming
Zhao, Yong-chao
[J]. 2015 INTERNATIONAL CONFERENCE ON NETWORK AND INFORMATION SYSTEMS FOR COMPUTERS (ICNISC), 2015, : 354 - 357
[9] MOOC for Medical Big Data Research An Important Role in Hypertension Big Data Research
Wang Xinyan
Tian Livuan
Xu Bo
Wang Xueliang
Wu Wenjun
[J]. 2015 IEEE FIRST INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING SERVICE AND APPLICATIONS (BIGDATASERVICE 2015), 2015, : 453 - 455
[10] The evolving field of Big Data: understanding geographic information systems analysis and its transformative potential in ophthalmic research
Soares, Rebecca Russ
[J]. CURRENT OPINION IN OPHTHALMOLOGY, 2022, 33 (03) : 188 - 194

← 1 2 3 4 5 →