most citedGrader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy

576 citations · 587 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2018★ 11 cited

Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program

Paisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse +29

Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical…

cs.CV2017★ 576 cited

Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy

Jonathan Krause, Varun Gulshan, Ehsan Rahimy +5

Diabetic retinopathy (DR) and diabetic macular edema are common complications of diabetes which can lead to vision loss. The grading of DR is a fairly complex process that requires…