Transforming Eye-Care Diagnostics Through Artificial Intelligence, Biometric Evaluation, and Tele-Optometry

Visual impairment remains a major global health concern associated with disorders such as diabetic retinopathy, glaucoma, cataract, and age-related macular degeneration. Early detection of ocular abnormalities remains essential for preventing irreversible visual loss. Conventional diagnostic methods rely on clinical examination and specialised imaging, yet limitations in accessibility, diagnostic variability, and delayed detection continue to affect effective eye-care delivery in many settings. Advances in digital technologies have introduced innovative diagnostic approaches integrating artificial intelligence (AI), ocular biometric evaluation, and tele-optometry to improve efficiency and reach of ophthalmic care. The objective of this review involves a comprehensive examination of recent developments in digital ophthalmic diagnostics, focusing on AI-based image analysis, biometric measurement technologies, and tele-optometry platforms. Relevant literature addressing AI applications, ocular biometric assessment, and remote ophthalmic screening systems was evaluated to synthesise current knowledge on diagnostic capability and clinical relevance. Current evidence indicates that AI algorithms enable automated interpretation of retinal images and facilitate early identification of ocular diseases. Biometric evaluation provides precise anatomical measurements that support refractive assessment and surgical planning. Tele-optometry systems expand diagnostic access through remote imaging and consultation services, improving screening coverage in underserved populations. Integration of AI, biometric technologies, and tele-optometry demonstrates strong potential to enhance disease detection, strengthen clinical decision support, and expand accessibility of ophthalmic diagnostic services.