Glaucoma

Accurate Prediction of Humphrey 10-2 Visual Fields in Glaucoma from a Single Rapid IMOvifa 24plus(1-2).

PURPOSE: Predicting the Humphrey Field Analyzer (HFA) 10-2 visual field (VF) using machine learning (ML) based on IMOvifa 24plus(1-2) VF data. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: Seventy actual IMOvifa 24plus(1-2) tests from 25 patients (The Jikei University School of Medicine) and 3472 synthesized IMOvifa 24plus(1-2) tests from 884 patients who underwent HFA 24-2 and HFA 10...

TADynFed: Dynamic modality-adaptive federated learning with tissue-aware disentanglement for cross-disease analysis.

Federated learning (FL) enables collaborative medical image analysis across decentralized institutions while preserving data privacy. However, real-world deployment faces critical challenges: modality heterogeneity, where clients possess incomplete or varying medical image modalities, and cross-disease generalization, requiring models to adapt to unseen pathologies with anatomical consistency. Exi...

Automated Report Generation in Ophthalmology: Integrating Artificial Intelligence, Multimodal Imaging, and Clinical Data.

Artificial intelligence (AI) has emerged as a transformative force in ophthalmology, enabling automated, accurate, and efficient clinical reporting. T...

Diagnosis of Primary Open-Angle Glaucoma Using Spectral Profiling of Aqueous Humor-Derived Exosomes.

Primary open-angle glaucoma (POAG) is one of the most common neurodegenerative diseases that cause irreversible optic nerve damage. POAG diagnosis req...

Global research status in the treatment of glaucoma: a systematic bibliometric analysis.

AIM: To present an overview of the research on global glaucoma treatment in the last decade in terms of publication year, journals, countries/regions,...

Opportunities and challenges in leveraging multiomics and biobanks for vision science.

PURPOSE OF REVIEW: Emerging biobank resources allow large-scale integration of eye-specific phenotypes with clinical, genomic, and multiomic data. Thi...

Improving Fairness and Mitigating Bias in Multicenter Electronic Health Records Models to Predict Glaucoma Outcomes.

PURPOSE: To evaluate the effectiveness and generalizability of bias mitigation methods in glaucoma progression prediction models across a multicenter ...

Advancing glaucoma care: What's new in the 6th edition of the European Glaucoma Society guidelines.

The 6th Edition of the European Glaucoma Society (EGS) Guidelines delivers a comprehensive, methodologically robust update to one of the most authorit...

Comprehensive Serum Proteomics Uncovers Epigenetic and Inflammatory Pathways Underlying Primary Open-Angle Glaucoma.

Glaucoma is a leading cause of irreversible blindness, driven by progressive Retinal ganglion cell loss and optic nerve degeneration. The molecular me...

Smartphone-Based Portable Slit Lamp in Anterior Segment Diseases: A Narrative Review of Clinical Assessment and Integration with Artificial Intelligence.

Smartphone-based portable slit lamps are rapidly evolving from simple add-ons into practical, low-cost front-line tools for anterior segment care beyo...

SwinCup-DiscNet: A fusion transformer framework for glaucoma diagnosis using optic disc and cup features.

Glaucoma remains a critical cause of permanent global visual disability, and is produced by advancing destruction of the visual nerve head (ONH). Earl...

Development of deep learning model to screen for primary open-angle glaucoma in African ancestry individuals.

Primary open-angle glaucoma (POAG) screening using artificial intelligence (AI) has emerged as a transformative method to identify undiagnosed disease...

Offline AI-assisted fundus imaging for preliminary screening of childhood glaucoma.

PURPOSE: To evaluate the feasibility and performance of AI-assisted portable fundus photography in children with glaucoma. METHODS: This case series d...

GDPooled transformer: glaucoma detection using pooled attention based transformer with attention mechanism.

Glaucoma is a common eye disease affecting several people worldwide. Blindness can be avoided with proper treatment and regular examination. Delayed d...

A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation.

Glaucoma is the leading cause of irreversible blindness worldwide with heterogeneous progression rates. Artificial Intelligence (AI) may enable accura...

A comparative evaluation of parafoveal and perifoveal macular vessel density loss in glaucoma using 3 × 3 mm OCTA scans.

In a prior study we demonstrated the strong performance of convolutional neural networks (CNNs) in distinguishing healthy from glaucomatous eyes and s...

Awareness, trust, and expectations of AI for glaucoma care among Bulgarian ophthalmologists: Role of demographic factors.

Artificial intelligence (AI) holds promise for enhancing glaucoma screening and management, yet its adoption depends on clinician perceptions, particu...

Ligand-based machine learning models to classify active compounds for prostaglandin EP2 receptor.

Prostaglandin receptors are pharmacologically validated targets with implications in several medical indications, including glaucoma, cardiac cyanotic...

Predicting HFA 30-2 Visual Fields with Deep Learning from Multimodal OCT-Fundus Feature Fusion and Structure-Function Discordance Analysis.

Glaucoma is a leading cause of irreversible vision loss. During clinical follow-up, visual field (VF) tests (Humphrey Field Analyzer 30-2) assesses fu...

Classifying retinal images via vascular-optic disc cross-segmentation and attentive feature selection.

The prevalence of retinal disorders is rising at an alarming rate, posing a significant risk of irreversible blindness without timely intervention. Re...