Ophthalmology

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

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Brain tumour histopathology through the lens of deep learning: A systematic review.

PROBLEM: Machine learning (ML)/Deep learning (DL) techniques have been evolving to solve more comple...

Utilizing natural language processing to identify pediatric patients experiencing status epilepticus.

PURPOSE: Compare the identification of patients with established status epilepticus (ESE) and refrac...

A vision-language foundation model for precision oncology.

Clinical decision-making is driven by multimodal data, including clinical notes and pathological cha...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to ...

Exploring the effect of gestational diabetes mellitus on retinal vascular morphology by PKSEA-Net.

BACKGROUND: Gestational diabetes mellitus (GDM) is a temporary metabolic disorder in which small ret...

ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer.

The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. ...

Graph neural networks in histopathology: Emerging trends and future directions.

Histopathological analysis of whole slide images (WSIs) has seen a surge in the utilization of deep ...

Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading.

Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, n...

Residual Self-Calibrated Network With Multi-Scale Channel Attention for Accurate EOG-Based Eye Movement Classification.

Recently, Electrooculography-based Human-Computer Interaction (EOG-HCI) technology has gained widesp...

A bird's-eye view of the biological mechanism and machine learning prediction approaches for cell-penetrating peptides.

Cell-penetrating peptides (CPPs) are highly effective at passing through eukaryotic membranes with v...

Investigating the role of large language models on questions about refractive surgery.

BACKGROUND: Large language models (LLMs) are becoming increasingly popular and are playing an import...

Predictive modeling of consecutive intravenous immunoglobulin treatment resistance in Kawasaki disease: A nationwide study.

Kawasaki disease (KD) is a leading cause of acquired heart disease in children, often resulting in c...

An effective vessel segmentation method using SLOA-HGC.

Accurate segmentation of retinal blood vessels from retinal images is crucial for detecting and diag...

Alzheimer's disease recognition using graph neural network by leveraging image-text similarity from vision language model.

Alzheimer's disease (AD), a progressive neurodegenerative condition, notably impacts cognitive funct...

Lesion classification and diabetic retinopathy grading by integrating softmax and pooling operators into vision transformer.

INTRODUCTION: Diabetic retinopathy grading plays a vital role in the diagnosis and treatment of pati...

Ocular Biometry OCR: a machine learning algorithm leveraging optical character recognition to extract intra ocular lens biometry measurements.

Given close relationships between ocular structure and ophthalmic disease, ocular biometry measureme...

Meibomian gland alterations in allergic conjunctivitis: insights from a novel quantitative analysis algorithm.

PURPOSE: To investigate the changes in meibomian gland (MG) structure in allergic conjunctivitis (AC...

Automatic segmentation of white matter lesions on multi-parametric MRI: convolutional neural network versus vision transformer.

BACKGROUND AND PURPOSE: White matter hyperintensities in brain MRI are key indicators of various neu...

Machine Learning Approaches in High Myopia: Systematic Review and Meta-Analysis.

BACKGROUND: In recent years, with the rapid development of machine learning (ML), it has gained wide...

A weak edge estimation based multi-task neural network for OCT segmentation.

Optical Coherence Tomography (OCT) offers high-resolution images of the eye's fundus. This enables t...

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