Artificial intelligence Refers to intelligent looking software. The AI algorithm is used to detect multiple optic diseases using deep learning. This AI system The aim is to help general practitioners and non-ophthalmic healthcare providers who need accurate and immediate assessment of their diseases. This article summarizes the current AI methods, eye imaging methods and key points. Eye diseases And the application of AI to screen them and facilitate promising AI projects in ophthalmology. The most intensive study is done Diabetic retinopathyGlaucoma, and AMD, which are further explained.
Diabetes affects approximately 415 million people worldwide, or one in eleven adults. It is the result of long-term diabetes and vasculitis which affects one third of people with diabetes and can lead to permanent blindness. In addition, to address this global disease, AI can be used to predict DR risk and progression in patients with diabetes. Using 52 optical coherence tomography (OCT) images, the DL-based computer-aided method detects DR with an AUC of 0.98. Even with good results in the cross-validation process, the system needs more validation in large groups of patients. CAD system based on CML algorithms that have good accuracy and AUC for autonomous identification of non-proliferative DR (NPDR) using optical coherence tomography angiography (OCTA) images.
In the industrial world, AMD is the leading cause of irreversible blindness in the elderly. The purpose of using the ML algorithm is to automatically identify AMD-related lesions to improve AMD diagnosis and treatment. ML has been used in SD-OCT and fundus images to detect druzen, fluid, reticulated pseudodrussen, and geographic atrophy. Accuracy is usually more than 80 percent, and the agreement between the model and retina specialists can exceed 90 percent. Multiple CML approaches have been used for automatic diagnosis and grading of AMD. However, the most significant work has been done in the last two years using DL approaches. DCNN appears to play a screening role in these studies, and its performance is comparable to that of physicians. Exudates, macular edema, Drucene, and choroidal neovascularization have all been detected automatically using the DL algorithm.
Glaucoma is the world’s third-largest eye-threatening disease and has serious implications for global blindness. Patients with glaucoma have high intraocular pressure, optic nerve head (ONH) damage, retinal nerve fiber layer (RNFL) defects, and progressive vision loss. Automated detection of glaucoma related symptoms is very important in its timely diagnosis. So far, DL-based Glucomatous Diagnosis models have been developed using Funds Pictures, VFs and Wide-Field OCT scans, and DL is better than CML in detecting preperimetric open-angle glaucoma (OAG) eyes.
The AI system aims to help general practitioners and non-ophthalmic healthcare providers who need accurate and immediate assessment of diseases and make significant contributions to the field of ophthalmology.
Dr. S Natarajan, Chief, Clinical Services, Aditya Jyot Eye Hospital, Dr. By a unit of Agarwal’s Eye Hospital.
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