Glaucoama diagnosis using machine learning methods

The research focuses on the usage of machine learning algorithms in glaucoma diagnostics. The objective is to analyze and compare various machine-learning algorithms by constructing classification systems that verify glaucoma in ICT photos. The study involves extracting features from images, classifying them using these features, and evaluating the effectiveness of methods. This approach provides insights into the creation of an automated glaucoma diagnostic system, contributing to a faster and safer medical process