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Automatic diagnosis of diabetic retinopathy using machine learning: a review

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dc.contributor.author Gunawardhana, PL
dc.contributor.author Jayathilake, R
dc.contributor.author Withanage, Y
dc.contributor.author Ganegoda, GU
dc.contributor.editor Karunananda, AS
dc.contributor.editor Talagala, PD
dc.date.accessioned 2022-11-16T03:55:26Z
dc.date.available 2022-11-16T03:55:26Z
dc.date.issued 2020-12
dc.identifier.citation P. L. Gunawardhana, R. Jayathilake, Y. Withanage and G. U. Ganegoda, "Automatic Diagnosis of Diabetic Retinopathy using Machine Learning: A Review," 2020 5th International Conference on Information Technology Research (ICITR), 2020, pp. 1-6, doi: 10.1109/ICITR51448.2020.9310818. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19513
dc.description.abstract Diabetic Retinopathy is a popular cause of diabetes, causing vision-impacting lesions of the retina. Blindness may be avoided by early detection. The ophthalmologist's manual approach of diagnosing diabetic retinopathy is expensive and time consuming. At the same time, unlike computer assisted diagnostic systems, it may cause misdiagnosis. Deep learning has recently become one of the most effective approaches that has obtained better efficiency in the analysis and classification of medical images. In medical image analysis, convolutional neural networks are more commonly used as a deep learning approach and they are extremely effective. This paper assessed and addressed the new state-of-the-art Diabetic Retinopathy color fundus image classification and detection methodologies using deep learning and machine learning techniques. Additionally, various challenging issues that need further study are also discussed. en_US
dc.language.iso en en_US
dc.publisher Faculty of Information Technology, University of Moratuwa. en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9310818 en_US
dc.subject Diabetic Retinopathy en_US
dc.subject Deep neural network en_US
dc.subject Convolutional neural network en_US
dc.subject Retinal fundus images en_US
dc.subject Machine learning en_US
dc.title Automatic diagnosis of diabetic retinopathy using machine learning: a review en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.year 2020 en_US
dc.identifier.conference 5th International Conference in Information Technology Research 2020 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.proceeding Proceedings of the 5th International Conference in Information Technology Research 2020 en_US
dc.identifier.doi 10.1109/ICITR51448.2020.9310818 en_US


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  • ICITR - 2020 [27]
    International Conference on Information Technology Research (ICITR)

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