Latest AI and machine learning research in ophthalmology for healthcare professionals.
The electroencephalogram (EEG) provides a direct measure of brain electrical activity but is typically contaminated by artifacts, most notably those arising from eye movements. Such artifacts are often removed using blind source separation techniques such as independent component analysis (ICA). However, it remains challenging to determine whether subtracting eye-movement-related components identi...
BackgroundIn minimally invasive surgery (MIS), maintaining consistent optical clarity is essential for surgical safety and efficiency. However, lens contamination events (LCEs) such as fogging and debris accumulation continue to disrupt visualization, requiring frequent camera removal and cleaning that prolongs operative time and is linked to surgical injuries.ObjectiveDetermine performance of an ...
The current study conducts extensive bibliometric analysis of pharmacology bibliometric publications worldwide during 2015-April 15, 2026. The objecti...
The multi-label retinal disease classification is a difficult one since fundus images might comprise many co-occurring abnormalities, extreme in relat...
BACKGROUND: Accurate measurement of minimum macular hole (MH) diameter is essential for diagnosis and treatment. The manual measurement approach by op...
Computer-assisted surgery research requires large, deeply annotated video datasets that capture clinical and technical variability. Existing cataract ...
This study comprehensively reviews human-machine collaborative decision-making (HMCD) methods and applications across management science, the military...
OBJECTIVE: Isolated rapid-eye-movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due ...
Clinical adoption of artificial intelligence (AI) in radiology has matured through task-specific tools for detection, segmentation, triage, and quanti...
We systematically map the evidence on optical coherence tomography (OCT) biomarkers-mainly disorganization of the retinal inner layers (DRIL), disrupt...
INTRODUCTION: Timely access to ophthalmological care is a challenge in primary health care (PHC). Teleophthalmology and artificial intelligence (AI) a...
Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosi...
Visual impairment (VI) is a growing condition associated with aging, neurological diseases, and chronic eye conditions. In 2023, more than 2.2Â billion...
Vision impairment remains a major global health challenge, and early diagnosis of retinal diseases is essential to prevent avoidable vision loss. Colo...
Feature representation learning in graph neural networks (GNNs) is a dynamic process driven by progressive information exchange throughout the graph. ...
Chronological age incompletely captures heterogeneity in biological aging. In this prospective study of 45,819 UK Biobank participants, we developed a...
Orbital fractures are frequently encountered in maxillofacial trauma and can be associated with severe globe injuries (SGI). Accurate and timely diagn...
BACKGROUND: Foundation models have shown promising performance in ophthalmology image analysis, but their ability to generalize to unseen imaging type...
The "Diabetic Retinal Disease (DRD) Cure Accelerator," a joint initiative by the Mary Tyler Moore Vision Initiative and the Collaborative Community on...
INTRODUCTION: Socially assistive humanoid robots have emerged as promising tools for enhancing mood, engagement, and social connection in clinical and...