Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

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Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology.

OBJECTIVE: With the development of day surgery, the characteristics of "short, frequent and fast" op...

HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.

Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventio...

Enhancing diabetic retinopathy diagnosis: automatic segmentation of hyperreflective foci in OCT via deep learning.

OBJECTIVE: Hyperreflective foci (HRF) are small, punctate lesions ranging from 20 to 50 m and exhib...

Capsule network-based deep learning for early and accurate diabetic retinopathy detection.

Glaucoma, an optic nerve disease resulting in blindness if left untreated, is a difficult condition ...

Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases.

Retinal images provide a non-invasive and accessible means to directly visualize human blood vessels...

An integrated approach for advanced vehicle classification.

This study is dedicated to addressing the trade-off between receptive field size and computational e...

Retinal fundus imaging-based diabetic retinopathy classification using transfer learning and fennec fox optimization.

Diabetic retinopathy (DR) is a serious complication of diabetes that can result in vision loss if un...

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem.

The purpose of this article is to evaluate the application of artificial intelligence (AI) from the ...

Organic Synaptic Transistors Based on a Semiconductor Heterojunction for Artificial Visual and Neuromorphic Functions.

Visual acuity is the ability of the biological retina to distinguish images. High-sensitivity image ...

Predicting visual field global and local parameters from OCT measurements using explainable machine learning.

Glaucoma is characterised by progressive vision loss due to retinal ganglion cell deterioration, lea...

Managerial myopia and its barrier to green innovation in high-pollution enterprises: A machine learning approach.

Green technology innovation has become a vital remedy in response to the world's growing ecological ...

Insights from the eyes: a systematic review and meta-analysis of the intersection between eye-tracking and artificial intelligence in dementia.

OBJECTIVES: Dementia can change oculomotor behavior, which is detectable through eye-tracking. This ...

Ultrafast on-site adulteration detection and quantification in Asian black truffle using smartphone-based computer vision.

Asian black truffle Tuber sinense (BT) is a premium edible fungus with medicinal value, but it is of...

Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.

Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fib...

Mathematical Modeling and Artificial Intelligence to Explore Connections Between Glaucoma and the Gut Microbiome.

Glaucoma is a major cause of irreversible blindness, with primary open-angle glaucoma (POAG) being ...

High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature Analysis.

An effective and highly accurate strabismus screening method is expected to identify potential patie...

SignFormer-GCN: Continuous sign language translation using spatio-temporal graph convolutional networks.

Sign language is a complex visual language system that uses hand gestures, facial expressions, and b...

Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.

Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for...

Improving reliability of movement assessment in Parkinson's disease using computer vision-based automated severity estimation.

BackgroundClinical assessments of motor symptoms rely on observations and subjective judgments again...

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