Developing Machine Learning Based Interactive System that Diagnoses Cataract, Glaucoma and Diabetic Retinopathy using Fundus Images
Our project aims to develop a machine learning-based interactive system that diagnoses cataract, glaucoma, and diabetic retinopathy using fundus images. In detail, we proposed a decision support system that is easy to use, benefiting from several machine learning algorithms in the background. Machine learning and deep learning algorithms such as Neural Network, SVM, gradient boost trained, and tested with publicly available datasets such as Messidor and EyePACS.
Slides from project presentation
