Deep Learning Technology for Retinal Disease Classification

This paper reviews techniques for automated retinal disease detection, which is important due to the increasing prevalence of eye diseases. These techniques include deep learning, machine learning, and transfer learning. The paper analyzes their strengths, weaknesses, and challenges and suggests research directions for improving accuracy. The goal is to help ophthalmologists diagnose and treat retinal diseases promptly, thus reducing the rate of sight loss