Identification Of Diabetic Retinopathy Classification Using Machine Learning Algorithms On Clinical Data And Optical Coherence Tomography Angiography

This article discusses the potential of machine learning algorithms to accurately classify diabetic retinopathy using OCTA parameters and clinical data. The study found that combining these two sources of information improved the sensitivity and specificity of computer-aided diagnosis. However, more research is needed in multiclass DR classification using ML algorithms.