Glaucoma

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progression with deep learning (DL).

A multi-label transformer-based deep learning approach to predict focal visual field progression.

PURPOSE: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression, which has not been explored in prior studies.

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography.

Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple ...

Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability.

PURPOSE: Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and st...

Prediction and Detection of Glaucomatous Visual Field Progression Using Deep Learning on Macular Optical Coherence Tomography.

PRCIS: A deep learning model trained on macular OCT imaging studies detected clinically significant functional glaucoma progression and was also able ...

Prediction model for elevated intraocular pressure risk after silicone oil filling based on clinical features.

BACKGROUND: To evaluate risk factors and further develop prediction models for intraocular pressure elevation (IOP) after vitreoretinal surgery with s...

Deep learning-based identification of eyes at risk for glaucoma surgery.

To develop and evaluate the performance of a deep learning model (DLM) that predicts eyes at high risk of surgical intervention for uncontrolled glauc...

AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.

The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photogr...

Artificial intelligence in glaucoma: opportunities, challenges, and future directions.

Artificial intelligence (AI) has shown excellent diagnostic performance in detecting various complex problems related to many areas of healthcare incl...

Artificial intelligence in glaucoma detection using color fundus photographs.

PURPOSE: To explore the potential of artificial intelligence (AI) for glaucoma detection using deep learning algorithm and evaluate its accuracy for i...

Evaluation of Verteporfin as a Novel Antifibrotic Agent in a Rabbit Model of Glaucoma Filtration Surgery: A Pilot Study.

PURPOSE: Verteporfin is a benzoporphyrin derivative which is Food and Drug Administration-approved for treatment of choroidal neovascularization in co...

Efficient feature selection based novel clinical decision support system for glaucoma prediction from retinal fundus images.

The process of feature selection (FS) is vital aspect of machine learning (ML) model's performance enhancement where the objective is the selection of...

Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.

PURPOSE: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and u...

Artificial intelligence for glaucoma: state of the art and future perspectives.

PURPOSE OF REVIEW: To address the current role of artificial intelligence (AI) in the field of glaucoma.

Exploring large language model for next generation of artificial intelligence in ophthalmology.

In recent years, ophthalmology has advanced significantly, thanks to rapid progress in artificial intelligence (AI) technologies. Large language model...

ChatGPT: is it good for our glaucoma patients?

PURPOSE: Our study investigates ChatGPT and its ability to communicate with glaucoma patients.

Predicting glaucoma progression using deep learning framework guided by generative algorithm.

Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how...

Editorial: Translational opportunities for AI in glaucoma.

Assessment of angle closure disease in the age of artificial intelligence: A review.

Primary angle closure glaucoma is a visually debilitating disease that is under-detected worldwide. Many of the challenges in managing primary angle c...

Computational methods in glaucoma research: Current status and future outlook.

Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and pot...