Latest AI and machine learning research in glaucoma for healthcare professionals.
Background: The visual field (VF) test results of many eyes with glaucoma progress despite treatment. This suggests that some eyes are either untreated or that the management of intraocular pressure (IOP) does not influence the outcome. In this work, we explore whether future VF parameters can be predicted from a baseline optical coherence retinal nerve fibre layer (OCT-RNFL) scan using a deep lea...
Objective To characterize the clinical and administrative concerns communicated through secure ophthalmology messaging and to assess differences in message content across patient sociodemographic groups. Design Cross-sectional study of de-identified, patient-initiated secure messages sent between June 2014 and July 2024. Participants Patients with ophthalmic conditions who initiated secure electro...
Estimating uncertainty in deep learning models is critical for reliable decision-making in high-stakes applications such as medical imaging. Prior res...
Glaucoma is a top cause of irreversible blindness globally, making early detection and longitudinal follow-up pivotal to preventing permanent vision l...
Electric field (EF) stimulation is an emerging neuromodulatory strategy for promoting the repair and functional recovery of degenerated neural network...
Abstract Purpose: Glaucoma, a leading cause of irreversible vision loss, often remains undiagnosed due to its asymptomatic progression and the limitat...
ImportanceVision-language models (VLMs) enable generalist multimodal reasoning, but their ability to resolve brief, low-contrast cues in surgical vide...
Test-Time Adaptation (TTA) has emerged as a promising solution for adapting a source model to unseen medical sites using unlabeled test data, due to...
Large language models (LLMs) can simulate clinical reasoning based on natural language prompts, but their utility in ophthalmology is largely unexpl...
Glaucoma is a leading cause of irreversible blindness, but early detection can significantly improve treatment outcomes. Traditional diagnostic meth...
The integration of deep learning-based glaucoma detection with large language models (LLMs) presents an automated strategy to mitigate ophthalmologi...
PURPOSE: Standard deep learning (DL) models often suffer significant performance degradation on out-of-distribution (OOD) data, where test data differ...
Glaucoma remains a leading cause of irreversible blindness worldwide, with early detection crucial for preventing vision loss. This study developed an...
This research work reveals the eye opening wisdom of the hybrid labyrinthine deep learning models synergy born out of combining a trailblazing convo...
Glaucoma is a group of serious eye diseases that can cause incurable blindness. Despite the critical need for early detection, over 60% of cases remai...
The scarcity of high-quality, labelled retinal imaging data, which presents a significant challenge in the development of machine learning models fo...
Glaucoma is an age-related neurodegenerative disease characterized by progressive optic nerve damage. Accelerated biological aging, assessed using pre...
Glaucoma is a leading cause of irreversible blindness worldwide; therefore, detection of this disease in its early stage is crucial. However, previous...
Deep learning algorithms as tools for automated image classification have recently experienced rapid growth in imaging-dependent medical specialties, ...
BACKGROUND: This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first i...