| The evidence for automated grading in diabetic retinopathy screening. | |
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MedLine Citation:
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PMID: 21644913 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening. |
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Authors:
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Alan D Fleming; Sam Philip; Keith A Goatman; Gordon J Prescott; Peter F Sharp; John A Olson |
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Publication Detail:
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Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Review |
Journal Detail:
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Title: Current diabetes reviews Volume: 7 ISSN: 1875-6417 ISO Abbreviation: Curr Diabetes Rev Publication Date: 2011 Jul |
Date Detail:
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Created Date: 2011-07-12 Completed Date: 2011-11-21 Revised Date: 2012-04-23 |
Medline Journal Info:
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Nlm Unique ID: 101253260 Medline TA: Curr Diabetes Rev Country: United Arab Emirates |
Other Details:
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Languages: eng Pagination: 246-52 Citation Subset: IM |
Affiliation:
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College of Life Science and Medicine, University of Aberdeen, Foresterhill, AB25 2ZD, Scotland. a.fleming@abdn.ac.uk |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Diabetic Retinopathy
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diagnosis* Humans Image Processing, Computer-Assisted / utilization* Mass Screening / methods Pattern Recognition, Automated / methods, utilization* Visual Field Tests / methods* |
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