title: The evidence for automated grading in diabetic retinopathy screening.
abstract: 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.
authors.affiliation: College of Life Science and Medicine, University of Aberdeen, Foresterhill, AB25 2ZD, Scotland. a.fleming@abdn.ac.uk
authors.forename: Alan D
authors.initials: AD
authors.lastname: Fleming
authors.forename: Sam
authors.initials: S
authors.lastname: Philip
authors.forename: Keith A
authors.initials: KA
authors.lastname: Goatman
authors.forename: Gordon J
authors.initials: GJ
authors.lastname: Prescott
authors.forename: Peter F
authors.initials: PF
authors.lastname: Sharp
authors.forename: John A
authors.initials: JA
authors.lastname: Olson
mesh_terms: D003930:Diabetic Retinopathy / Q000175:diagnosis*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods / Q000706:statistics & numerical data*; D058609:Visual Field Tests / Q000379:methods*