Glaucoma

Improving Generalization of Deep Learning for Glaucoma Classification Under Real-World Domain Shift via Unsupervised Domain Adaptation.

PURPOSE: To develop and evaluate an unsupervised domain adaptation (UDA) framework for glaucoma classification from fundus images that improves the generalizability of deep learning (DL) models across heterogeneous imaging characteristics and clinical settings. METHODS: We developed an adversarial UDA framework that adapts a labeled source domain to an unlabeled target domain by jointly optimizing...

Smartphone-Based Fundus Imaging in Global Eye Care: Closing the Gap.

Smartphone-based fundus imaging (SBFI) is an emerging approach with potential relevance for global ophthalmic care, including in low- and middle-income countries and other resource-constrained settings. This scoping review, based on a structured literature search, synthesises current SBFI technology, clinical and teaching applications, implementation challenges and future directions. Analysing 30 ...

Evaluation of Large Language Model-Generated Recommendations in Glaucoma Surgical Decision-Making.

OBJECTIVE: To evaluate the utility, rationality, and safety of glaucoma surgery recommendations generated by three prominent large language models (LL...

Performance and label efficiency of traditional deep-learning models and a retina-specific foundation model for ocular and systemic disease detection: a retrospective comparative study.

BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison w...

Labeling matters: A multicenter machine learning study on visual field progression in Glaucoma.

BACKGROUND: To compare machine learning (ML) performance for detecting visual field (VF) progression across different labeling strategies using a larg...

Artificial intelligence for healthcare in Nepal: A scoping review of clinical applications, implementation evidence, and health-system governance.

BACKGROUND: Nepal offers a distinctive LMIC setting for evaluating AI-health adoption due to its difficult geography, specialist shortage, high case b...

Research Progress of Diabetes-related Glaucoma: Mechanisms, Impacts and Management Strategies.

Diabetes mellitus (DM), a highly prevalent metabolic disorder, is increasingly recognised for its significant association with glaucoma, a leading cau...

A decade of artificial intelligence research in ophthalmology: Global trends and transferable insights for medical AI.

To characterize global trends in ophthalmic AI research from 2015-2025 and drive transferable insights into the broader evolution of AI in medicine, w...

A Risk Prediction Model for Normal-Tension Glaucoma Progression Integrating Genetic Markers and Corneal Biomechanics.

OBJECTIVE: Normal-tension glaucoma (NTG) is characterized by progressive optic nerve damage despite intraocular pressure remaining consistently within...

Comparative Image-Based Evaluation of Deep Learning Models for the Diagnosis of Different Ocular Diseases in Cats.

Ocular pathologies are a leading cause of visual impairment in cats and require accurate, timely diagnosis for effective treatment. This study aimed t...

Applications of artificial intelligence in rural ophthalmology: a scoping review.

OBJECTIVE: Artificial intelligence (AI) is increasingly utilized for screening within ophthalmology, yet its application in rural communities remains ...

An artificial intelligence-driven workflow to detect the macula and quantify retinal ganglion cells in nonhuman primates.

The retinal ganglion cell layer integrates and transmits stimuli from photoreceptors to the central nervous system. Retinal ganglion cell loss is a ha...

Reply to Comment on An Artificial Intelligence-Based Prognostic Model for Prediction of Functional Glaucoma Progression From Clinical and Structural Data.

Exploratory multivariate adaptive regression splines modeling of myopic progression in children receiving atropine.

BACKGROUND: The increasing global prevalence of pediatric myopia has led to the widespread use of atropine for myopia control. Despite its proven effi...

Comment on An Artificial Intelligence-Based Prognostic Model for Prediction of Functional Glaucoma Progression From Clinical and Structural Data.

A Comparison of Machine Learning and Human Graders for Glaucoma Diagnosis from Fundus Images for Population Screening.

PURPOSE: To compare the accuracy of vertical cup-disc ratios (VCDR), ascertained by machine learning (ML) versus human graders, from fundus images for...

Abnormal functional lateralization and cooperation in primary angle-closure glaucoma correlate with cell type-specific transcriptional signatures.

BACKGROUND: Primary angle-closure glaucoma (PACG) damages retinal ganglion cells (RGCs) and is associated with neurodegeneration. This study used rest...

Comparative evaluation of large language models and clinicians in real-world glaucoma clinical reasoning.

PURPOSE: Clinical decision-making in glaucoma is complex and requires integration of heterogeneous information, including patient history, examination...

[Concepts and clinical application of digital 3D microscopy].

BACKGROUND: Heads-up 3D surgery is becoming increasingly more important in ophthalmic microsurgery. Digital 3D visualization systems supplement tradit...

Multimodal foundation model assistance for differentiating primary open-angle glaucoma in highly myopic eyes.

PURPOSE: To develop and evaluate a multimodal foundation-model-assisted system for differentiating primary open-angle glaucoma (POAG) from non-glaucom...