Glaucoma Prediction Using Supervised Learning

• Published in: International Conference on Computer Communication and Informatics (Online) pp. 1 - 6
• Main Authors: Suganthe, R.C., Geetha, M., Latha, R.S., Preethi, S., Rishika, M., Sandhiya, D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23.01.2023
• Subjects: Classification; component; Convolutional Neural Network; Deep Learning; Glaucoma; Machine Learning; Preprocessing; Random Forest; Segmentation; Support Vector Machine
• ISSN: 2473-7577
• DOI: 10.1109/ICCCI56745.2023.10128405

Glaucoma is an eye disorder when the optic nerve suffers damage due to an increase in intraocular fluid pressure. When there is too much fluid present or the channel in the eye through which the fluid normally drains is blocked, pressure builds up. People blind due to glaucoma and estimated that 4.5 million people globally affected by glaucoma. Among all global blindness, blindness happen by glaucoma is slightly more than 12%. It is the second most frequent reason for blindness in the globe. Percent of affected people that are not even aware of having glaucoma, may up to 50% in developed countries and may rise to 90%in undeveloped parts of the world. So, detection of glaucoma is a crucial role in life Glaucoma can be detected using increased cup to disc ratio where optic cup is a cup in the center of the optic disc. The optic disk is the circular area inside the eye where the optic nerve connects to the retina. The Glaucoma prediction can be done with Machine Learning, Deep Learning Techniques. The proposed work proposes Convolutional Neural Network algorithm which gives a great classification performance when compared to other algorithms such as Support Vector Machine (SVM) and Random Forest.