Scientists from LETI trained a neural network to detect retinal pathology that occurs with diabetes from a photo of the eye. This tool can also serve for early diagnosis of diabetes. The Ministry of Education and Science told socialbites.ca about this.
“We have developed a mathematical model that can be used to detect diabetic retinopathy in the early stages of the disease using retinal images with 88.7% accuracy. And since this pathology is a consequence of a violation of the normal level of glucose in the blood, the neural network can also be used for early diagnosis of diabetes,” project leader Ali Sultan Maeya, graduate student of the Department of Biotechnical Systems from the Petersburg Electrotechnical University “LETI” told socialbites.ca.
Diabetic retinopathy is retinal damage that occurs in people with diabetes between the ages of 20 and 65 and can lead to vision loss. The main symptoms include decreased vision, flickering stars, discomfort and pain in the eyes, and blurred vision. However, often the disease is asymptomatic at first, making it difficult to detect in the early stages – this problem can be solved by the development of LETI.
The model created by scientists can recognize diabetic retinopathy with symptoms such as bleeding in eye photographs, lipid (fat) accumulation, enlargement of blood vessels and thinning of their walls.
“In the future, it is possible to develop a device in the form of glasses that can automatically scan the eye, find the region of the retina using artificial intelligence and evaluate not only the stage of diabetic retinopathy but also the stage of other diseases of the eye associated with diabetes: cataracts, glaucoma,” says Ali Sultan Maya.
Currently, the authors are collecting more information about the anatomy of the fundus, assessment methods, and their automation to improve diagnostic accuracy using artificial intelligence.
Previous scientists I learnedHe said that 6 percent of people can get rid of type 2 diabetes by losing weight.
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Source: Gazeta
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