Morbi et tellus imperdiet, aliquam nulla sed, dapibus erat. Aenean dapibus sem non purus venenatis vulputate. Donec accumsan eleifend blandit. Nullam auctor ligula

Get In Touch

Quick Email
[This article belongs to Volume - 26, Issue - 05]


The progress in digital health and telemedicine has brought forth instruments can enhance the accessibility and efficacy of eye care services. Current research shows how technology-enabled approaches are changing the way that care is provided. Traditional diagnostic methods rely on physician expertise, resulting in high misdiagnosis rates and data inefficiency. Integrating ophthalmology with artificial intelligence (AI) promises to overhaul current diagnostic approaches, potentially making a significant clinical impact. Deep Learning (DL), an emerging facet of machine learning (ML), uncovers complex data structures without explicit rule specifications. The review centers on the revolutionary potential of artificial intelligence (AI) in the identification and treatment of ocular disorders, such as diabetic retinopathy, degenerative maculopathy, retinal diseases, corneal diseases, anterior ocular region issues, and glaucoma. It explores AI-driven advancements in image analysis, pattern recognition, and machine learning techniques for individualized treatment plans, early diagnosis, and categorization. The difficulties with data standards, interpretability, and integration are discussed in this paper. into clinical practice. It also emphasizes the potential of AI to enhance screening efficiency, reduce physician workload, and improve patient outcomes in ocular pathologies.