Artificial intelligence could be harnessed to diagnose refractive error from retinal fundus images.
Researchers trained an algorithm to predict refractive error with high accuracy from a total of 226,870 retinal fundus images, and validated it on two datasets: UK Biobank and the US Age-Related Eye Disease Study (AREDS).
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An overview of the background and current treatment options available for the macular diseases retinal vein occlusion, diabetic macular oedema and age-related macular degeneration.
