Convolutional Neural Networks for Diabetic Retinopathy
- Submitting institution
-
The University of Liverpool
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 12043
- Type
- E - Conference contribution
- DOI
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10.1016/j.procs.2016.07.014
- Title of conference / published proceedings
- Procedia Computer Science
- First page
- 200
- Volume
- 90
- Issue
- -
- ISSN
- 1877-0509
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 139
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the outcome of an interdisciplinary collaboration between Coenen and Harding (Professor of Clinical Ophthalmology). The aim is to utilise machine learning for "point of care" analysis of retina image data to diagnose Diabetic Retinopathy, which is a major cause of blindness if left undiagnosed. This paper was the first to successfully apply Convolutional Neural Networks to the five class Diabetic Retinopathy classification problem, and thereby influenced a large body of subsequent work.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -