A Review on Machine Learning Methods in Diabetic Retinopathy Detection
Journal of Ophthalmic and Optometric Sciences,
Vol. 5 No. 1 (2021),
19 Mehr 2022
,
Page 52-66
https://doi.org/10.22037/joos.v5i1.39216
Abstract
Ocular disorders have a broad spectrum. Some of them, such as Diabetic Retinopathy, are more common in low-income or low-resource countries. Diabetic Retinopathy is a cause related to vision loss and ocular impairment in the world. By identifying the symptoms in the early stages, it is possible to prevent the progress of the disease and also reach blindness. Considering the prevalence of different branches of Artificial Intelligence in many fields, including medicine, and the significant progress achieved in the use of big data to investigate ocular impairments, the potential of Artificial Intelligence algorithms to process and analyze Fundus images was used to identify symptoms associated with Diabetic Retinopathy. Under the studies, the proposed models for transformers provide better interpretability for doctors and scientists. Artificial Intelligence algorithms are also helpful in anticipating future health issues after appraising premature cases of the ailment. Especially in ophthalmology, a trustworthy diagnosis of visual outcomes helps physicians in advising disease and clinical decision-making while reducing health management costs.
- Artificial Intelligence
- Diabetic Retinopathy
- Deep Learning
- Fundus Images
- Machine Learning
How to Cite
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