Peer-reviewed · IJERT · 2026 · Open access
Eye Diseases Detection Using Machine Learning Models
Md Tanvir Chowdhury, Md Fahad Mia, Anindita Sutradhar, Md Khalid Mahbub Khan, Abu Talha
International Journal of Engineering Research & Technology (IJERT), Vol. 14, Issue 05 (IIRA 5.0 (2026)), published 2026-05-24
Compares EfficientNetB0, VGG19, and MobileNetV2 for classifying four ocular conditions (cataract, diabetic retinopathy, glaucoma, and normal) from fundus images, measured by accuracy, precision, recall, F1-score, and loss. EfficientNetB0 performed best, reaching 98.5% training accuracy and 94.2% validation accuracy while mitigating overfitting.
Md Tanvir Chowdhury, Md Fahad Mia, Anindita Sutradhar, Md Khalid Mahbub Khan, Abu Talha (2026). Eye Diseases Detection Using Machine Learning Models. International Journal of Engineering Research & Technology (IJERT), 14(05), IIRA 5.0 (2026). https://doi.org/10.17577/IJERTCONV14IS050007