  Diabetic retinopathy is an ocular condition that affects individuals with
diabetes mellitus. It is a common complication of diabetes that can impact the
eyes and lead to vision loss. One method for diagnosing diabetic retinopathy is
the examination of the fundus of the eye. An ophthalmologist examines the back
part of the eye, including the retina, optic nerve, and the blood vessels that
supply the retina. In the case of diabetic retinopathy, the blood vessels in
the retina deteriorate and can lead to bleeding, swelling, and other changes
that affect vision. We proposed a method for detecting diabetic diabetic
severity levels. First, a set of data-prerpocessing is applied to available
data: adaptive equalisation, color normalisation, Gaussian filter, removal of
the optic disc and blood vessels. Second, we perform image segmentation for
relevant markers and extract features from the fundus images. Third, we apply
an ensemble of classifiers and we assess the trust in the system.
