It employs support vector machines (SVM) and logistic regression. The machine learning model is trained using the four extracted characteristics, which are the cup area, disc area, CDR, and rim width.

In recent years, deep learning has emerged as a transformative tool, offering automated, efficient, and reliable methods for both the detection and classification of cataract severity.

Diagram of the deep learning models. Upper: Deep learning model ... Damon Wing Kee W, Tien Yin W, Jiang L. Glaucoma detection based on deep convolutional neural network. Conf Proc IEEE Eng ...

Elevated intraocular pressure is the hallmark of glaucoma, which can cause vision loss and optic nerve damage if initially undiagnosed due to mild symptoms. For vision impairment to be effectively ...

Glaucoma is an eye condition that causes the retina to slowly deteriorate over time. If the disease is detected early enough, its progression can be stopped. Unfortunately, early diagnosis is rare ...

It presents the AI-based Glaucoma Screening (AI-GS) network, a system that integrates multiple lightweight deep learning models to analyze fundus images. The AI-GS network detects early structural ...

MINNEAPOLIS — A deep learning model trained on fundus photographs showed promise in the detection of severe glaucoma, with lower accuracy in mild to moderate cases, according to a poster ...