A machine learning model was developed to predict the risk of diabetic retinopathy based on heavy metal exposure data. The model identified urinary Sb…
Browsing: Diabetic Retinopathy
A study found that existing deep learning models can capture clinically important incidental pathology in fundus photographs misclassified as diabetic retinopathy. This suggests a…
This article discusses a study that used non-mydriatic fundus cameras and AI software to detect diabetic retinopathy in patients. The study found that the…
Artificial Intelligence (AI) has been widely adopted in various domains, such as healthcare, finance, education, and industry. AI encompasses several branches, including machine learning…
This article presents a review of various deep and machine learning techniques used to identify various complications in diabetic retinopathy (DR). The authors propose…
Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss due to damage to the blood vessels in the retina. Early retinal…
Artificial Intelligence (AI) has been around for more than 50 years, but recent advances in deep learning have made it more powerful and accessible.…
QC Ware, a leading quantum software and services company, announced the results of a joint research project with one of the world’s leading biotechnology…