Oct 2021 – In the recent years, EyRIS’ SELENA+ has proven its worth in the early detection of retinal eye diseases across 24 countries. SELENA+’s success represents our first steps to revolutionize healthcare delivery through deep technology.
In our next chapter, EyRIS is excited to introduce another Deep Learning Algorithm (DLA), this time to detect Chronic Kidney Disease (CKD). Jointly developed by the clinicians and scientists from the Singapore Eye Research Institute and the National University of Singapore (NUS) School of Computing, this new DLA can detect the early stages of CKD through automated analysis of fundus retinal images.
It is estimated that 10% of the population worldwide is affected by chronic kidney disease (CKD). Obese individuals and those with diabetes and hypertension are especially susceptible to kidney damage. Early stages of CKD have proven difficult to detect as patients usually present little to no symptoms. The current conventional approach in screenings involves syringes and needles which can deter some people. Left untreated, advanced CKD can result in the need for dialysis or even kidney transplant.
This technology deploys deep learning on big data and clinical assessment techniques that studies the tortuosity of blood vessels in the retina. Concurrently, the algorithm runs multiple iterations to achieve high sensitivity and specificity which is vital to crown this diagnostic aid as a viable and cost-effective alternative to detect CKD.
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