Glaucoma, a leading cause of irreversible blindness worldwide, presents substantial challenges in clinical diagnosis and long-term management due to its often insidious early progression and the irreversible nature of late-stage optic nerve damage. However, rapid advancements in artificial intelligence technologies, particularly in machine learning, deep learning, and large language models, are transforming ophthalmic practice. AI is now being extensively applied across the spectrum of glaucoma care, from screening and precise diagnosis to optimizing treatment and supporting long-term patient management. This review systematically examines the latest applications of AI in glaucoma, highlighting multidimensional innovations. These applications span a wide range, including sophisticated image analysis, the identification of novel molecular biomarkers, prediction of treatment response, and advanced surgical planning. The paper also discusses key challenges and future development directions of these technologies, aiming to provide new insights for glaucoma management.
Jiaqi Zhang (2025) studied this question.