Ophthalmology

Artificial intelligence derived grading of mustard gas induced corneal injury and opacity.

Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessing corneal damage due to chemical injury in live rabbits remains lacking. This study aimed to develop an AI-derived clinical classification model for an objective grading of corneal injury and opacity levels in live rabbits following ocular exposure ...

Interpretable longitudinal glaucoma visual field estimation deep learning system from fundus images and clinical narratives.

Glaucoma is a globally prevalent disease that leads irreversible blindness. The visual field (VF) examination is important but time-consuming for visual function evaluation with high requirement of cooperation and reliability of patients. While color fundus photographs (CFPs) are easy to access. Here, we proposed a multi-modal longitudinal estimation deep learning (MLEDL) system, capable of predic...

Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care.

There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We develope...

Deep learning quantifies pathologists' visual patterns for whole slide image diagnosis.

Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole sl...

A deep convolutional neural network-based novel class balancing for imbalance data segmentation.

Retinal fundus images provide valuable insights into the human eye's interior structure and crucial features, such as blood vessels, optic disk, macul...

Machine learning unveils hypoxia-immune gene hub for clinical stratification of thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO) is an autoimmune disorder affecting the orbit, potentially resulting in blindness. This study focused on the r...

EEG based real time classification of consecutive two eye blinks for brain computer interface applications.

Human eye blinks are considered a significant contaminant or artifact in electroencephalogram (EEG), which impacts EEG-based medical or scientific app...

Transformer attention fusion for fine grained medical image classification.

Fine-grained visual classification is fundamental for medical image applications because it detects minor lesions. Diabetic retinopathy (DR) is a prev...

Large language models provide discordant information compared to ophthalmology guidelines.

To evaluate the agreement of LLMs with the Preferred Practice Patterns (PPP) guidelines developed by the American Academy of Ophthalmology (AAO). Open...

Perilesional dominance: radiomics of multiparametric MRI enhances differentiation of IgG4-Related ophthalmic disease and orbital MALT lymphoma.

BACKGROUND: To develop and validate a diagnostic framework integrating intralesional (ILN) and perilesional (PLN) radiomics derived from multiparametr...

Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson's disease patients.

BACKGROUND: Traditional clinical diagnostic methods of rapid eye movement sleep behavior disorder (RBD) have certain limitations, especially in the ea...

Ensemble machine learning algorithm for anti-VEGF treatment efficacy prediction in diabetic macular edema.

BACKGROUND: Diabetic macular edema (DME) is a leading cause of vision loss in diabetes, with variable responses to anti-vascular endothelial growth fa...

A versatile framework for attitude tuning of beamlines at light source facilities.

Aside from regular beamline experiments at light sources, the preparation steps before these experiments are also worthy of systematic consideration i...

An intelligent screener for mild cognitive impairment via integrated eye-tracking and the digital clock drawing test.

BackgroundMild cognitive impairment (MCI) is a risk factor for dementia, and early screening is crucial for patient prognosis.ObjectiveTo construct an...

Cognition-Eye-Brain Connection in Alzheimer's Disease Spectrum Revealed by Multimodal Imaging.

BACKGROUND: The connection between cognition, eye, and brain remains inconclusive in Alzheimer's disease (AD) spectrum disorders.

CIAA: Integrated Proteomics and Structural Modeling for Understanding Cysteine Reactivity with Iodoacetamide Alkyne.

Cysteine residues play key roles in protein structure and function and can serve as targets for chemical probes and even drugs. Chemoproteomic studies...

Artificial Intelligence-Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs.

BACKGROUND: Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, mo...

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UNLABELLED: Early detection of glaucoma represents a vital factor in securing vision while the disease retains its position as one of the central caus...

Integrating multi-omics and machine learning for disease resistance prediction in legumes.

Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legu...

Screening of Glaucoma in High-Risk Minority Populations.

PRECIS: This chapter reviews the current recommendations on screening for open angle glaucoma in Black and Hispanic populations. Strategies for increa...