Ophthalmology and Vision Science

Artificial Intelligence in Vision Screening and Diagnostics

Artificial intelligence is rapidly transforming vision screening, diagnostics, and clinical decision-making in ophthalmology. Machine learning algorithms analyze imaging data from retinal scans, optical coherence tomography, and fundus photography to detect early signs of glaucoma, diabetic retinopathy, macular degeneration, and other ocular conditions. AI improves diagnostic accuracy, reduces interobserver variability, and enables predictive modeling for disease progression. Challenges include data privacy, algorithm validation across diverse populations, and integration into routine clinical workflows. Nanotechnology-enhanced imaging devices and sensors support AI-based diagnostics by providing high-resolution and precise measurements. Regulatory agencies evaluate AI tools for safety, efficacy, and clinical applicability to ensure patient protection. Emerging trends focus on real-time automated screening, remote diagnostics via telemedicine, and AI-assisted personalized treatment planning. By leveraging artificial intelligence, ophthalmologists can enhance early detection, optimize patient management, expand access to care, and reduce the global burden of preventable vision loss, while adhering to strict regulatory and ethical standards.