Artificial intelligence in the management of ocular diseases: opportunities, challenges, and future directions

ABSTRACT Introduction Artificial Intelligence (AI), a hallmark of modern computational science, refers to the use of computer algorithms to emulate human intelligence. The field of ophthalmology involves an extensive use of digital imaging and objective datasets; thus, AI can help in early detection of ocular diseases like diabetic retinopathy and glaucoma, by processing retinal, fundus, and optical coherence tomography scans with a high level of precision. AI ultimately aids in understanding alterations in nerve health, visual field, cup-to-disc ratio, and retinal vascular parameters. Areas covered This review provides an updated view of the application of AI in the management of ocular diseases, drawing insights from a plethora of literature and research studies. Additionally, the significant progress made by AI in the domain of drug delivery and ophthalmic surgery has also been explored. The review also addresses the unmet gaps and challenges faced in implementing AI. Expert opinion Enormous research is still ongoing to maximize AI’s versatility across multiple applications. The use of sophisticated machine learning (ML) and deep learning (DL) algorithms has already become an integral part of ophthalmology. This convergence holds revolutionizing capabilities in diagnostic, screening, and even surgical workflows, ultimately allowing clinicians to garner their attention toward patient care. GRAPHICAL ABSTRACT