Ophthalmology

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

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WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification.

Weed detection and classification using computer vision and deep learning techniques have emerged as...

Generative artificial intelligence for fundus fluorescein angiography interpretation and human expert evaluation.

Fundus fluorescein angiography (FFA) is the gold standard for diagnosing chorioretinal diseases, but...

A comparative analysis of DeepSeek R1, DeepSeek-R1-Lite, OpenAi o1 Pro, and Grok 3 performance on ophthalmology board-style questions.

The ability of large language models (LLMs) to accurately answer medical board-style questions refle...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its iden...

Quantitative Mapping of Oxygen Affinity to Local Chemical Environments in Ti-Zr-Nb-Ta Alloys via Machine Learning.

Simultaneously enhancing strength and ductility is a longstanding challenge in materials science. Re...

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 variabl...

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 peril...

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...

Transformer attention fusion for fine grained medical image classification.

Fine-grained visual classification is fundamental for medical image applications because it detects ...

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),...

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 r...

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 ...

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

Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial sup...

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 glau...

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) ex...

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 diagn...

Enhancing occluded and standard bird object recognition using fuzzy-based ensembled computer vision approach with convolutional neural network.

Classifying bird species is essential for ecological study and biodiversity protection, currently, c...

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG.

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges...

Plant leaf disease detection using vision transformers for precision agriculture.

Plant diseases cause major crop losses worldwide, making early detection essential for sustainable f...

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