Artificial intelligence (AI) is being widely used to detect different Multiple optic disorders. Diabetic retinopathy (DR), non-proliferative DR (NPDR), Age-related macular degeneration (AMD), and glaucoma are some of them.Diabetes affects over 415 million people worldwide, and one-third of diabetics have vasculopathy, which can lead to lifelong blindness due to diabetic retinopathy (DR). The risks and progression of DR can be studied using 52 optical coherence tomography (OCT) images using AI, further it can be diagnosed using deep learning (DL)-based computer-aided technique (CAD). Non-proliferative DR (NPDR) could also be identified quite accurately using a CAD system based on CML algorithms that used optical coherence tomography angiography (OCTA) pictures to an accuracy of more than 80%.

Newly developed computer-based deep learning (DL)-based glaucomatous diagnosis models have resulted in better outcomes than chirp managed laser (CML) at diagnosing preperimetric open-angle glaucoma (OAG) eyes. They used fundus images, VFs, wide-field OCT scans etc.Other diseases such as Age-related macular degeneration (AMD) could be easily diagnosed using Machine learning (ML) algorithms and automatically identify AMD-related lesions. In Spectral Domain Optical Coherence Tomography (SD-OCT) and fundus images, Machine learning (ML) has been utilized to detect drusen, fluid, reticular pseudodrusen, and geographic atrophy.

Thus, the AI system is designed to assist general physicians and non-ophthalmic healthcare providers who require accurate and immediate disease assessment and who wish to make a substantial contribution to the field of ophthalmology. (ETHealthWorld, June 03, 2022)