Advancement in Diabetic Retinopathy Prediction: Utilizing Voting Classifiers Techniques for Early Detection
Abstract
Diabetic Retinopathy (DR), also known as diabetic eye disease, damages the retina and is linked to diabetes mellitus. According to previous studies, DR influences up to 80% of individuals and children who have had type I and II diabetes for more than 20 years. However, with proper care and cautious eye monitoring, severe blind forms of retinopathy and maculopathy can be avoided. This study used a voting classifier, combining the predictions of base models, such as Support Vector Machine (SVM), Random Forest (RF), and Gradient-Boosting (GB) classifiers, to improve the performance and accuracy of predictions.
Fields of Study & Subjects
Retinal Imaging and Analysis
Artificial Intelligence in Healthcare
Retinal Diseases and Treatments
Publication details
- Journal / source
- Engineering Technology & Applied Science Research
- Volume
- 16
- Issue
- 1
- Pages
- 31464–31468
- Publication date
- 9 February 2026
- Language
- EN