Ophthalmology

A compact neuromorphic system for ultra-energy-efficient, on-device robot localization.

Neuromorphic computing offers a transformative pathway to overcome the computational and energy challenges faced in deploying robotic localization and navigation systems at the edge. Visual place recognition, a critical component for navigation, is often hampered by the high resource demands of conventional systems, making them unsuitable for small-scale robotic platforms, which still require accu...

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2176 combinatorially generated shapes embossed into polymers using an unbiased screen. This identified microtopographies that, in vitro, reduce colon...

Sustainability and minimization of carbon footprint in ophthalmology: what can we change in the outpatient clinic routine?

Ophthalmological care has significant potential to consume energy, utilize resources, and generate waste, thereby contributing to a substantial portio...

Smartphone eye-tracking with deep learning: Data quality and field testing.

Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial i...

Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review.

Macular pigment (MP) is a crucial pigment in the macular region. It plays an important role in filtering blue light, and exhibits anti-inflammatory an...

Artificial intelligence for glaucoma.

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the accuracy of artificial intelligence (AI) algori...

Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system.

OBJECTIVE: This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adole...

Artificial intelligence versus ophthalmology experts: Comparative analysis of responses to blepharitis patient queries.

ObjectiveTo assess the accuracy and clinical education value of responses from AI models (GPT-3.5, GPT-4o, Gemini, Gemini Advanced) compared to expert...

Early detection and staging of retinitis pigmentosa using multifocal electroretinogram parameters and machine learning algorithms.

Retinitis pigmentosa is an inherited retinal disease caused by damage to photoreceptor cells. Diagnosis and staging of this disease are crucial for ea...

Multimodal personalization of transcranial direct current stimulation for modulation of sensorimotor integration.

Transcranial direct current stimulation (tDCS) for the modulation of smooth pursuit eye movements provides an ideal model for investigating sensorimot...

Artificial intelligence for age-related macular degeneration diagnosis in Australia: A Novel Qualitative Interview Study.

INTRODUCTION: Artificial intelligence (AI) systems for age-related macular degeneration (AMD) diagnosis abound but are not yet widely implemented. AI ...

Retinal Vessel Traits and Age-Related Eye Disease in the Canadian Longitudinal Study on Aging.

BACKGROUND: To cross-sectionally and longitudinally examine whether retinal vessel traits are associated with glaucoma-related outcomes (glaucoma, cup...

Integrating explainable machine learning and transcriptomics data reveals cell-type specific immune signatures underlying macular degeneration.

Genome-wide association studies (GWAS) have established key role of immune dysfunction in Age-related Macular Degeneration (AMD), though the precise r...

Lumbar spinal stenosis: current concept of management.

Lumbar spinal stenosis (LSS) is a common degenerative spinal condition where spinal canal narrowing causes symptoms such as neurogenic claudication, r...

The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis.

Thorough investigations of end-users' awareness, acceptance, and concerns about ophthalmic artificial intelligence (AI) are essential to ensure its su...

Detecting optimal gaze behavior of successful basketball free throwing via machine learning system.

Eye tracking in sport is an emerging field that explores the relationships between visual function and motor performance. However, research has shown ...

High-Performance Broadband Integrated Detection System for Multifunctional Applications.

In the digital era, photodetectors have become indispensable components in optical communication, imaging, and artificial intelligence, driven by the ...

Benchmarking test-retest variability in microperimetry for intermediate age-related macular degeneration using MP-3 and MAIA.

OBJECTIVE: Microperimetry (MP) has emerged as a clinical functional endpoint in nonexudative age-related macular degeneration (AMD). In this study, we...

Exploring the limit of image resolution for human expert classification of vascular ultrasound images in giant cell arteritis and healthy subjects: the GCA-US-AI project.

OBJECTIVES: Prompt diagnosis of giant cell arteritis (GCA) with ultrasound is crucial for preventing severe ocular and other complications, yet expert...

DNA-based prediction of eye color in Latin American population applying Machine Learning models.

Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relat...