EYE DISEASES CLASSIFICATION USING DEEP LEARNING
International Research Journal of Modernization in Engineering Technology and Science · 2023
This paper proposes a deep learning-based approach for the automatic classification of eye diseases.The eyes are one of the most important organs in the human body, responsible for vision and many critical functions.Therefore, it is essential to diagnose and treat eye diseases promptly to prevent vision loss and related complications.However, traditional methods of eye disease detection are time-consuming, costly, and often require trained professionals, making them inaccessible to many people.The proposed approach utilizes deep learning techniques to classify eye diseases accurately and efficiently.Specifically, the deep learning model is trained on a large dataset of images of healthy and diseased eyes to learn features and patterns that distinguish different eye diseases.The trained model can then classify new images of eyes into one of the pre-defined categories of diseases, allowing for timely and accurate diagnosis.The importance of eye disease detection cannot be overstated, as it can prevent or reduce the risk of vision loss and related complications.Early detection can also lead to more effective treatment and management of eye diseases.Additionally, color blindness is a common condition that affects many people worldwide.Therefore, the proposed approach includes a color blindness test as part of the eye disease classification system to identify individuals with this condition.Overall, the proposed deep learning-based approach has the potential to revolutionize eye disease detection and improve the quality of eye care globally.