Glaucoma

To see or not to see the vet: A vignette-based study of decision-making by UK dog owners regarding seeking veterinary care for commonly presenting conditions.

Barriers to accessing veterinary-care for dog-owners are diverse and dynamic, and widely accepted as major canine welfare threats because of potential non-, under- or delayed treatment. Owner knowledge and perceptions are recognised as key influences on decisions to seek veterinary-care but are currently understudied. This study aimed to explore decision-making by UK dog-owners around seeking vete...

Artificial Intelligence in Neurology and Neuro-Ophthalmology: Current Applications and Future Directions.

Artificial intelligence (AI) is revolutionizing neuro-ophthalmology by enhancing diagnostic accuracy and clinical decision-making. Techniques like deep learning, convolutional neural networks, and transfer learning effectively detect conditions such as optic neuropathies, papilledema, and glaucoma through imaging analysis. AI also supports patient triage, monitors disease progression, and streamli...

Reply to Commentary on ``Development and Evaluation of an Artificial Intelligence Model to Set Target IOP for Glaucoma''.

Comment on: ``Development and Evaluation of an Artificial Intelligence Model to Set Target IOP for Glaucoma''.

Artificial Intelligence-Guided Endpoint Selection for Neuroprotection Trials in Glaucoma.

OBJECTIVE: Standard Automated Perimetry (SAP) is the primary method for monitoring glaucoma progression and an established functional endpoint in clin...

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

PURPOSE: Integration of various sources of information for prediction of disease progression is an unmet need in glaucoma diagnostics. We designed a d...

Convolutional Graph Isomorphism Network to Detect Glaucomatous Visual Field Defects.

PURPOSE: To evaluate the performance of a deep learning (DL) model based on graph isomorphism networks (GINs) for detecting glaucomatous visual field ...

Evaluation of Glaucoma Treatment Information on Social Media Using Large Language Models.

PRCIS: This study investigates the accuracy, readability, utility, and educational value of glaucoma treatment content on social media platforms and e...

Big data in ophthalmology: comparative databases and research applications.

PURPOSE OF REVIEW: This review aims to highlight the expanding role of big data in ophthalmology, provide a comparison of the most prominent databases...

Anterior segment optical coherence tomography imaging in angle closure: advances in diagnosis and care.

PURPOSE OF REVIEW: To highlight emerging applications of anterior segment optical coherence tomography (AS-OCT) in the diagnosis, risk stratification,...

Comparison of RETFound and a Supervised Convolutional Neural Network for Detection of Referable Glaucoma from Fundus Photographs.

PURPOSE: To compare the performance of a vision transformer-based foundation model (RETFound) and a supervised convolutional neural network (VGG-19) f...

Accuracy and Readability of Chat Generative Pre-Trained Transformer-4 Omni in Answering Ophthalmology Patient Questions.

PURPOSE: To assess the quality of Chat Generative Pre-Trained Transformer-4 Omni (ChatGPT-4o) responses to questions submitted by patients through Epi...

Detecting Inflammation in Fundus Photographs Using Machine Learning.

PURPOSE: To utilize a machine learning model for employing ultra-widefield fundus photograph (UWFFP) as a surrogate marker for ultra-widefield fluores...

A systematic review of vision and vision-language foundation models in ophthalmology.

BACKGROUND: Vision and vision-language foundation models, a subset of advanced artificial intelligence (AI) frameworks, have shown transformative pote...

Advancements in ocular blood flow imaging: Clinical applications of laser speckle flowgraphy and optical coherence tomography angiography in retinal and choroidal vascular diseases.

Ocular blood flow imaging techniques have become indispensable in current clinical practice because retinal vascular disturbances have been implicated...

Global Trends and Emerging Themes in Tele-Ophthalmology Research: A Bibliometric Analysis (1993 to 2024).

BACKGROUND: Tele-ophthalmology is transforming eye care delivery, particularly in remote and underserved areas, where specialist shortages and geograp...

Impact of artificial intelligence in vision science: A systematic review of progress, emerging trends, data domain quantification, and critical gaps.

The prominence of artificial intelligence (AI) is growing exponentially, yet its implementation across research domains is uneven. To quantify AI tren...

DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation.

Retinal vascular morphology plays a crucial role in diagnosing diseases such as diabetes, glaucoma, and hypertension, making accurate segmentation of ...

Improvement of an eye disease detection model by using the denoising diffusion implicit model.

With rapid developments in artificial intelligence (AI), the discussion about and applications of generative AI have increased substantially. Generati...

A Semi-supervised Reinforcement Learning Framework Incorporating the Multi-scale IncepMambaNet Network for Glaucoma Progression Prediction.

Glaucoma is the leading cause of irreversible blindness worldwide. Currently, artificial intelligence (AI) technology combined with optical coherence ...