Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images

Abstract

AutoML models created by ophthalmologists without coding experience can detect RVO, RP and RD in UWF images with very good diagnostic accuracy. The performance was comparable to bespoke deep-learning models derived by AI experts for RVO and RP but not for RD.