IDx-DR, AI Application in Diabetic Retinopathy
Before when deep learning was not displayed in ophthalmology, diabetic retinopathy was needed to be evaluated and prescribed through human effort.
IDx-DR is using the algorithm which applied two development operating set (high specificity & high sensitivity) to identify diabetic retinopathy and to evaluate patient’s common status.
Referable and non-referable diabetic retinopathies were evaluated by two clinical validation sets (EYEPACS-1 & MESSIDOR-2) and ophthalmologists identified if these sets worked properly.
Multiple grading processes of convolutional neural networks along with data sets are required to get high sensitivity and specificity of RDR.
An overall sensitivity was lower than expectation, but FDA allowed to save more patients who were suffered by diseases.
The reference standard which used for this study was derived from ophthalmologist graders, and this will not find subtle traits which most ophthalmologists would not identify.