Ophthalmology

Computer-vision research powers surveillance technology.

An increasing number of scholars, policymakers and grassroots communities argue that artificial inte...

Leveraging retrieval-augmented large language models for patient education in ophthalmology.

Mechanism of cognitive style effects on hazard recognition of construction workers: A machine learning-aided approach.

BackgroundHazard recognition is a critical skill for construction workers and primarily consists of ...

A computer vision-based approach for high-throughput automated analysis of Arabidopsis seedling phenotypes.

Phenotype observations are common methodologies in plant biology studies, ranging from recording gro...

Disrupted functional topology of the white matter connectome in rhegmatogenous retinal detachment: insights from graph theory and machine learning.

BACKGROUND: Rhegmatogenous retinal detachment (RRD) is known to induce functional alterations in the...

StarNet: Indian star gooseberries dataset for quality and maturity assessment.

Star gooseberry provides immense health benefits and is widely recognized in the Indian medicinal sy...

Towards a comprehensive characterization of arteries and veins in retinal imaging.

Retinal fundus imaging is crucial for diagnosing and monitoring eye diseases, which are often linked...

Recognizing American Sign Language gestures efficiently and accurately using a hybrid transformer model.

Gesture recognition plays a vital role in computer vision, especially for interpreting sign language...

Real-world faricimab switch in France: artificial intelligence-based detection of changes in exudative signs in difficult-to-treat neovascular age-related macular degeneration.

PURPOSE: Some patients with neovascular age-related macular degeneration (nAMD) have persistent sign...

AI in Medical Questionnaires: Innovations, Diagnosis, and Implications.

This systematic review aimed to explore the current applications, potential benefits, and issues of ...

Integrating ocular and clinical features to enhance intravenous glucocorticoid response prediction in thyroid eye disease: a machine learning approach.

PURPOSES: Predicting intravenous glucocorticoid (IVGC) efficacy in thyroid eye disease (TED) is vita...

A multimodal visual-language foundation model for computational ophthalmology.

Early detection of eye diseases is vital for preventing vision loss. Existing ophthalmic artificial ...

Comparison of a novel gamified binocular therapy and standard monocular patching therapy in treating unilateral amblyopia in young children: a prospective, multicenter, randomized controlled trial.

BACKGROUND: Amblyopia is a leading cause of visual impairment in children, and conventional treatmen...

Designing Clinical Decision Support Systems (CDSS)-A User-Centered Lens of the Design Characteristics, Challenges, and Implications: Systematic Review.

BACKGROUND: Clinical decision support systems (CDSS) have the potential to play a crucial role in en...

MVKD-Trans: A Multi-View Knowledge Distillation Vision Transformer Architecture for Breast Cancer Classification Based on Ultrasound Images.

Breast cancer is the leading cancer threatening women's health. In recent years, deep neural network...

Cost-effective instruction learning for pathology vision and language analysis.

The advent of vision-language models fosters interactive conversations between artificial intelligen...

Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases.

BACKGROUND: Surgical errors in ophthalmology can have devastating consequences. We developed an arti...

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 applica...

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 w...

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-biofoul...

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

Neuromorphic computing offers a transformative pathway to overcome the computational and energy chal...