Big data and ophthalmic research
dc.contributor.author | Clark, Antony | |
dc.contributor.author | Ng, J. | |
dc.contributor.author | Morlet, N. | |
dc.contributor.author | Semmens, James | |
dc.date.accessioned | 2017-01-30T12:54:11Z | |
dc.date.available | 2017-01-30T12:54:11Z | |
dc.date.created | 2016-06-15T19:30:18Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Clark, A. and Ng, J. and Morlet, N. and Semmens, J. 2016. Big data and ophthalmic research. Survey of Ophthalmology. 61 (4): pp. 443-465. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/26575 | |
dc.identifier.doi | 10.1016/j.survophthal.2016.01.003 | |
dc.description.abstract |
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. | |
dc.title | Big data and ophthalmic research | |
dc.type | Journal Article | |
dcterms.source.volume | 61 | |
dcterms.source.startPage | 443 | |
dcterms.source.endPage | 465 | |
dcterms.source.issn | 0039-6257 | |
dcterms.source.title | Survey of Ophthalmology | |
curtin.department | Centre for Population Health Research | |
curtin.accessStatus | Fulltext not available |
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