Ophthalmology

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

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Hybrid attention-based deep learning for multi-label ophthalmic disease detection on fundus images.

BACKGROUND: Ophthalmic diseases significantly impact vision and quality of life. Early diagnosis usi...

Synthetic data in medicine: Legal and ethical considerations for patient profiling.

Synthetic data is increasingly used in healthcare to facilitate privacy-preserving research, algorit...

Evaluating anti-VEGF responses in diabetic macular edema: A systematic review with AI-powered treatment insights.

Recent advances in deep learning and machine learning have greatly increased the capabilities of ext...

Eyes Are the Windows to the Soul: Reviewing the Possible Use of the Retina to Indicate Traumatic Brain Injury.

Traumatic brain injury (TBI) induces complex molecular and cellular responses, often leading to visi...

Multi-Scale Vision Transformer with Optimized Feature Fusion for Mammographic Breast Cancer Classification.

: Breast cancer remains one of the leading causes of mortality among women worldwide, highlighting t...

Deep Learning Differentiates Papilledema, NAION, and Healthy Eyes with Unsegmented 3D OCT Volumes.

OBJECTIVE: Deep learning (DL) has been used to differentiate papilledema from healthy eyes and optic...

Leveraging computer vision systems for monitoring hutch-housed dairy calves.

Computer vision systems (CVS) have emerged as a powerful technology for animal monitoring. However, ...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Our study aims to improve the prediction performance of machine learning (ML) models by addressing f...

RadCLIP: Enhancing Radiologic Image Analysis Through Contrastive Language-Image Pretraining.

The integration of artificial intelligence (AI) with radiology signifies a transformative era in med...

RETINA: Reconstruction-based pre-trained enhanced TransUNet for electron microscopy segmentation on the CEM500K dataset.

Electron microscopy (EM) has revolutionized our understanding of cellular structures at the nanoscal...

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.

BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (...

Explainable Deep Learning System for Automatic Detection of Thyroid Eye Disease using Facial Images.

PURPOSE: To report an explainable deep learning (XDL) system to automatically detect thyroid eye dis...

Rapid diagnosis of TERT promoter mutation using Terahertz absorption spectroscopy in glioblastoma.

Glioblastoma (GBM) is a highly aggressive brain tumor with poor outcomes and limited treatment optio...

Comparison of ChatGPT-4, Microsoft Copilot, and Google Gemini for Pediatric Ophthalmology Questions.

PURPOSE: To evaluate the success of Chat Generative Pre-trained Transformer (ChatGPT; OpenAl), Googl...

A hybrid explainable federated-based vision transformer framework for breast cancer prediction via risk factors.

Breast cancer remains a leading cause of mortality in women, underscoring the need for timely and ac...

A bibliometric evaluation of scientific productivity in meibomian gland dysfunction research.

CLINICAL RELEVANCE: Meibomian gland dysfunction (MGD) is a major contributor to dry eye disease, aff...

Prediction of Myopia Among Undergraduate Students Using Ensemble Machine Learning Techniques.

BACKGROUND AND AIMS: Myopia is a prevalent refractive error, particularly among young adults, and is...

Early detection of retinal and choroidal microvascular impairments in diabetic patients with myopia.

PURPOSE: To evaluate and quantify diabetes-related retinal and choroid perfusion changes in individu...

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