Deep learning (DL), especially Convolutional neural networks (CNN), has gained wide popularity in various image processing tasks. With the significant achievements obtained in DL, it has provided many successful solutions for real-world applications as well as in medical domain. Automated retinal images analysis has been widely applied to screening Diabetic retinopathy (DR), which can greatly help preventing the occurrence of complete blindness when used in the early screening. In this paper, we mainly focus on DL, and we will give an overview of the deep learning-based methods for DR screening. Finally, we will discuss the main issues encountered in the DR screening systems.