Ophthalmology

Prognostic Imaging Biomarkers in Diabetic Macular Edema Treated with Anti-VEGF: A Multicenter AI Perspective.

INTRODUCTION: This study aimed to identify optical coherence tomography (OCT) biomarkers at baseline and after the loading phase (LP) of antivascular endothelial growth factor (VEGF), predictive of 12 months (12 m) morpho-functional outcomes in diabetic macular edema (DME). METHODS: This multicenter, retrospective study involved treatment-naive DME eyes treated with anti-VEGF agents. The OCT volum...

MRI-based automated segmentation and multiparametric quantification for assessing orbital soft tissue involvement in thyroid eye disease.

OBJECTIVES: To develop a deep learning-based multimodal framework for automated segmentation of orbital soft tissues and identify quantitative imaging biomarkers for precise grading of thyroid eye disease (TED). MATERIALS AND METHODS: This retrospective multicenter study enrolled 330 TED patients from a primary center for model development and 113 patients from two external centers for validation....

Multimodal deep learning prediction of treatment response to anti-vascular endothelial growth factor in diabetic macular oedema.

OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth...

Artificial intelligence applications in OCT and OCTA for diabetic retinopathy: A systematic review.

PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide. Optical coherence tomography (OCT) and OCT angiography (OCTA) pr...

Benchmarking resting state fMRI connectivity pipelines for classification: robust accuracy despite processing variability in cross-site eye state prediction.

The rapid evolution of machine learning (ML) methods has yielded promising results in human brain neuroscience. However, the reproducibility of ML app...

Fractal-domain Vision Graph Neural Network for Remote Sensing Ground Target Classification.

To the best of our knowledge, this paper is the first to integrate fractal signal processing with vision graph neural networks, establishing a new gra...

Classification of retinal diseases based on optical coherence tomography angiography using cross-modal transfer learning of domain-specific foundation AI models.

AIMS: This study evaluated the use of ophthalmic foundation deep-learning models with cross-modal transfer learning to classify multiple diseases on o...

Topology-preserving, diameter-specific framework for conjunctival vessel segmentation and tortuosity analysis in diabetes.

Diabetes is associated with progressive microvascular remodelling, commonly assessed using retinal imaging, yet alternative non-invasive vascular biom...

Urban-scale facade material mapping from street view images using vision-language models for circular construction planning.

The lack of reliable building-level data remains an obstacle for advancing urban sustainability and circular economy practices. Here, we present URBAN...

Smartphone gaze-tracking for accessible psychiatric assessment.

Eye movements are promising biomarkers for psychiatric and neurological disorders, yet conventional recording methods rely on bulky, expensive, and la...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

BACKGROUND: Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophanc...

Deep Learning-Assisted Room-Temperature Phosphorescence Sensor Array Based on Host-Guest Doping for Visual Discrimination of Triazole Fungicides.

Detection and discrimination of structurally similar triazole fungicide (TF) subtypes remain highly desirable yet challenging. This work presents a st...

The aging eye: navigating molecular mechanisms and innovative interventions.

The global demographic shift toward aging has precipitated a surge in age-related ocular pathologies, imposing a formidable public health challenge th...

The Evolving Landscape of Vision Rehabilitation: Current Status and Future Directions.

Vision impairment is increasingly recognised as a complex condition shaped not only by ocular pathology but also by cognitive, psychological, social a...

Explainable AI-driven diagnosis model for early glaucoma detection using grey-wolf optimized extreme learning machine approach.

Glaucoma is a leading global cause of blindness, making early detection essential. This paper introduces GlaucoXAI (Glaucoma Explainable AI), an advan...

Mapping the body: poetic metaphor and AI imaging in Carol Ann Duffy's 'The Map-Woman'.

This article offers an interdisciplinary analysis of Carol Ann Duffy's poem 'The Map-Woman', examining the metaphor of the female body as a map in rel...

Machine learning-optimized graphene-integrated refractory metasurface for broadband solar energy harvesting.

A graphene-integrated refractory metasurface absorber is proposed for broadband solar thermal energy conversion. Near-unity broadband absorptance acro...

Predictive robot eyes shape visual attention, performance, and trust in interaction with an industrial CoBot.

Collaborative robots increasingly share workspaces with humans, making the predictability of robot actions critical for efficient and safe coordinatio...

GPT-5-assisted versus expert surgeon refractive planning in smooth incision lenticule keratomileusis (SILK): comparative analysis and visual outcomes.

PURPOSE: To assess the performance of GPT-5 in refractive surgery planning by comparing its recommendations with expert surgeons and reporting visual ...

Smart label-free SPR biosensing platform for hemoglobin and urine glucose detection via machine learning.

This article presents the design and the numerical analysis of a smart label-free Surface Plasmon Resonance (SPR) sensor to detect the concentration o...