Adaptive machine learning classification for diabetic retinopathy

• Published in: Multimedia tools and applications Vol. 80; no. 4; pp. 5173 - 5186
• Main Authors: Math, Laxmi, Fatima, Ruksar
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2021; Springer Nature B.V
• Subjects: Annotations; Blindness; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Diabetes; Diabetic retinopathy; Diagnostic systems; Image classification; Lesions; Machine learning; Multimedia Information Systems; Object recognition; Segments; Sensitivity; Special Purpose and Application-Based Systems; Diabetic retinopathy; CNN (convolution neural networks); DL (deep learning); Fundus images

Diabetic retinopathy is the main cause of the blindness worldwide. However, the diabetic retinopathy is hard to be detected in the initial stages, and the procedure of diagnostic can be time-consuming even for experienced-experts. The segment based learning approach has shown the benefits over learn...