Neuro-ophthalmology and Vision Impairment: Understanding the Neural Basis of Visual Disorders - Deora, Ravindra Singh; Devi, Varsha; Saini, Neha Omprakash; Dhakad, Rajkumar; Kumawat, Mohit; Kumar Verma, Mahendra; Ali, Arshad (Journal of Neonatal Surgery, 2025)
Neuro-ophthalmic disorders that cause vision impairment create major difficulties for medical practitioners. Artificial intelligence (AI) advances through technological development introduced new ways to detect and track and handle medical conditions by analyzing complicated visual and neural information precisely. Neural visual disorder detection and treatment improvement requires understanding of visual disorder origins therefore this paper examines AI applications in neuro-ophthalmology for diagnosing and managing neural dysfunction-related visual disorders. Potentially disease patterns along with prognostic forecasts and treatment plan improvements form key capabilities demonstrated by AI according to the research. The research team performed an extensive review of present-day artificial intelligence solutions within neuro-ophthalmology where they evaluated machine learning systems alongside deep learning processes and neural network systems which operate for medical diagnostics and prognosis functions and bespoke treatment selection. The study presents both optical coherence tomography (OCT) and magnetic resonance imaging (MRI) as AI-assisted imaging solutions which improve diagnostic precision. The automation features in diagnosis as well as predictive disease forecasting and patient-specific treatment suggestions emerge from AI technology applications. AI assistive tools remain promising for vision rehabilitation because they improve the lives of people with limited eyesight. However AI usage faces organizational and ethical barriers in neuro-ophthalmology together with rigorous validation requirements and regulatory compliance. The successful implementation of AI in clinical practice needs joint efforts from multiple medical fields and ethical management standards to maintain open systems and priorities patients above all.Further research should concentrate on better AI algorithm development along with expanded data modal combination and strict observation of ethical and regulatory needs. AI collaboration together with neuro-ophthalmic clinical experience will redefine modern vision healthcare which results in better patient results.