كشف مرض اعتلال الشبكية لمرضى السكري باستخدام خوارزمية نظام الدعم الالي = Detecting diabetic retinopathy using Support Vector Machines

Abstract

Diabetic retinopathy (DR) is a vascular disease of the retina which affects patients with diabetes mellitus. It is the number one cause of blindness in people between the ages of 20-64. Diabetes mellitus is extremely common, so it is not surprising that DR affects 3.4 percent of the population. The goal of this research to classify patients having diabetic retinopathy or not having, we used dataset contains features extracted from the Messidor image database. All features represent either a detected lesion, a descriptive feature of an anatomical part or an image-level descriptor. In this research we used datasets from messidor database and SVM (Support Vector Machines) algorithm was used. The experiment was done on two different tools ,namely R programming and python and different results were obtained , as SVM algorithm was included by R programming achieved an accuracy of 74.78% with precision 86.66% and recall 71.23% ,when using SVM algorithm was included by python achieved accuracy was obtained 78.44% with precision 83.33% and recall 66.03%.unfortunately ,we did not achieve accuracy due to luck of data and incorrect handling of it ,therefore ,we recommend that you use more data and better processing technologies in the future.