Introduction: An Overview of Glaucoma

Civelekler Mustafa, Citirik Mehmet

DeepSeek AI outperformed other models in generating glaucoma PubMed citations, but all AI models produced errors, highlighting the need for human verification to prevent citation inaccuracies.

Hong Yanggang, Mi Yuze, Shu Wanyi et al.

Court Helen, Dougall Jacquie, Pooley Janet

Foster Paul J, Aung Tin, Friedman David S

Younis Danah A, Richter Grace M

Dietary nitrates, retinols, and Mediterranean diet reduce glaucoma risk, with combined healthy eating potentially offering the most benefit for optic nerve health.

Ayoubi Mohammad, Sayed Mohamed S, Khodeiry Mohamed M et al.

Big data in ophthalmology, using diverse databases, is transforming research by enabling AI, uncovering systemic links, and improving precision medicine for glaucoma and other conditions.

Hamzeh Nikoo, Lidder Alcina K, Feder Robert S et al.

ChatGPT-4o accurately answered most patient ophthalmology questions, but often at a 12th-grade reading level. Prompting for a 6th-grade level improved readability without losing accuracy, suggesting potential for patient education tools.

Zhao Dongyang, Fang Huihui, Gao Qi et al.

This study developed a multi-modal AI system for glaucoma grading, showing significantly improved accuracy by combining multiple eye scans, offering a more precise diagnostic tool for clinicians.

Lewallen Colby F, Ortolan Davide, Reichert Dominik et al.

This study found AI in vision science is heavily focused on image analysis, particularly for AMD/DR, but lags in cataract research, highlighting data and ethical challenges for broader clinical integration.

Pham Kenneth, Salowe Rebecca, Di Rosa Isabel et al.

Glaucoma was linked to a 23% higher dementia risk, particularly Alzheimer's and vascular dementia, with varying associations across glaucoma subtypes and APOE genotypes, highlighting a potential neurodegenerative connection.

Gupta Dhruva, Wagner Sarah L, Castillejos Ellenthal Alexandra G et al.

GPT models (GPT-4o, GPT-4o Mini) outperformed Gemini Pro in accurately and comprehensively answering patient glaucoma questions. This suggests GPT models offer valuable, high-quality health information, highlighting AI's potential for patient education.

Pazos Marta, Traverso Carlo E, Viswanathan Ananth

The 6th EGS Glaucoma Guidelines update evidence, expert consensus, and patient perspectives for optimal glaucoma diagnosis and management, providing a crucial resource for clinicians.

Yang Albert, Cano Jennifer, Xu Benjamin et al.

This study found reduced conjunctival venular blood flow dynamics (velocity, shear rate, stress) in glaucoma patients, suggesting endothelial dysfunction. This non-invasive measure could be a novel biomarker for glaucoma's vascular damage.

Qu Yanlin, Zhang Guanran, Wu Zhenyu et al.

This study found socioeconomic deprivation amplifies glaucoma risk from ultrafine particle exposure. Increasing greenness may mitigate this health disparity, especially in deprived areas.

Peixoto Ricardo D S, Pipis Spyros, Giannouladis Konstantinos et al.

Dhablania Nathan, Torres Mina, Burkemper Bruce et al.

This study found 22% of African Americans with eye disease were undiagnosed. Diabetes, infrequent eye exams, and trouble getting glasses were key predictors, highlighting the need for targeted screening to reduce vision loss.

Jin Kai, Yu Tao, Grzybowski Andrzej

Multimodal AI in ophthalmology, including for glaucoma, shows superior diagnostic performance (4-7% higher accuracy) than unimodal systems, offering more comprehensive and accurate clinical insights.

McGwin Gerald, Owsley Cynthia

Nassiri Nariman, Wilson M Roy

This review found targeted glaucoma screening in high-risk Black and Hispanic populations is useful and cost-effective, especially leveraging new technologies to improve access and case-finding.