And here comes the good news for patients suffering from diabetes facing related complications. It is a deep learning algorithm capable of interpreting signs of DR in retinal photographs. This new potential technique is great for doctors as it will help them to screen more patients, especially in underserved communities with restricted funds.
The techniques used previously are laser and anti-VEGF therapy factor in efficacy, safety, cost, and pragmatic issues. Google research team began studying whether machine learning could be used to screen for diabetic retinopathy (DR).
This study was published in the Journal of the American Medical Association. This paper demonstrates the technology benefits. It is estimated that the deep neural networks can be trained, using large data sets and without having to specify lesion-based features, to identify diabetic retinopathy or diabetic macular edema in retinal fundus images with high sensitivity and high specificity.
These results demonstrate that deep neural networks can be trained, using large data sets and without having to specify lesion-based features, to identify diabetic retinopathy or diabetic macular edema in retinal fundus images with high sensitivity and high specificity.
However, this algorithm has been trained to identify only diabetic retinopathy and diabetic macular edema.
News Source: BetaNews
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