Ophthalmology

Artificial intelligence and clinical informatics in UK ophthalmology training: a national cross-sectional survey.

BACKGROUND: Artificial intelligence (AI) and clinical informatics (CI) are strategic priorities for UK ophthalmology, with the Royal College of Ophthalmologists identifying education and training as central to safe implementation. However, formal CI/AI training is not currently embedded within the Ophthalmic Specialty Training (OST) curriculum. This study aimed to evaluate trainees' baseline knowl...

Beyond anxiety reduction: Psychological transformation and systemic contradictions in generative-AI-mediated language learning - A cultural-historical activity theory perspective.

This study explores the psychological transformation and contradictions arising from Generative AI (Gen-AI)-mediated language learning. Using Cultural-Historical Activity Theory (CHAT) as an analytical lens-operationalized through Engeström's (2015) activity system triangle to analyze interactions among system components and identify multi-level contradictions-the research examines how Gen-AI resh...

Bridging laboratory findings and artificial intelligence for the design of TlInTe2 crystals.

In our laboratory a specially designed Bridgman technique was utilized to pre- pare single crystals of TlInTe2. The structure of TlInTe2 in powder for...

Quantitative Analysis of Retinal Fluid by a Deep Learning Model in Uveitic Macular Edema.

OBJECTIVE: To assess whether artificial intelligence (AI)-derived fluid volume provides prognostic value for visual outcomes in uveitic macular edema ...

Precise Staging of Diabetic Retinopathy Through Machine Learning Analysis of Leakage Source Characteristics: A Radiomics-Driven Approach Integrating OCT-A and FFA.

INTRODUCTION: Evaluating retinal fundus image for diabetic retinopathy (DR) assessment is used to reduce the risk of blindness among diabetic patients...

Enhancing diabetic retinopathy diagnosis and grading: a retrospective study on AI-assisted decision making and cost analysis.

BACKGROUND/AIMS: Diabetic retinopathy (DR) is a major ocular complication of diabetes mellitus. While artificial intelligence (AI)-based DR screening ...

Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review.

This scoping review examines the existing literature on the application of artificial intelligence (AI) in screening for eye diseases, with a focus on...

Artificial Intelligence for Materials Science: Transforming Research Paradigms.

The evolution of materials science is undergoing a profound paradigm shift driven by artificial intelligence (AI), transitioning from traditional intu...

Artificial intelligence in the care of systemic lupus erythematosus: Current capabilities and translational barriers.

BackgroundThe clinical heterogeneity of systemic lupus erythematosus exceeds the resolution of conventional disease activity instruments. Artificial i...

AI-driven green processing and life cycle assessment for sustainable perovskite solar cells.

Despite rapid advances in perovskite solar cells, solvent selection remains a central determinant of safety, process robustness, and end-of-life outco...

Quantifying regional contributions to sex classification from fundus photographs via a two-stage attention-based deep learning approach.

This study quantitatively assesses the relative contribution of anatomically defined retinal regions (macula, optic disc, and retinal vasculature) to ...

Multisource Machine Learning Model for Detecting Referral-Warranted Retinopathy of Prematurity.

PURPOSE: To develop a multisource machine learning model for detecting referral-warranted retinopathy of prematurity (RW-ROP) using retinal images and...

Artificial intelligence and neurodegeneration: state of the art and explainability.

BACKGROUND: Alzheimer disease (AD) and Parkinson disease (PD) are an increasing healthcare concern and growing cause of disability in our century. The...

Nanostructured High-Entropy Yolk-Shell Oxides Platform for Efficient Metabolic Profiling of Diabetic Retinopathy.

Diabetic retinopathy (DR) is a leading cause of blindness in middle-aged and elderly populations worldwide, and its diagnosis remains challenging due ...

Assessing the clinical deployability of AI tools for caries detection: A structured narrative synthesis and proposed framework.

OBJECTIVE: To synthesise how studies evaluating AI-based caries detection on bitewing radiographs report evidence relevant to real-world clinical use ...

A clinically interpretable deep learning pipeline for diabetic retinopathy classification using EfficientNet, advanced data augmentation and GradCAM.

BACKGROUND: Early and reliable grading of diabetic retinopathy is important for preventing avoidable vision loss. Although deep learning methods have ...

A multi-agent system for automating scientific discovery.

Scientific discovery is driven by the iterative process of observation, hypothesis generation, experimentation, and data analysis. Despite recent adva...

[Vasomics: an emerging omics discipline for deciphering vascular health and disease].

The vascular system serves as the central architecture of the human circulatory network, whose structural and functional integrity is vital for mainta...

Machine Learning to Predict Outcomes of Anti-VEGF Therapy in Neovascular Age-Related Macular Degeneration.

OBJECTIVE: To develop machine learning models using OCT fluid metrics to predict long-term anti-VEGF treatment intensity and visual acuity (VA) outcom...

Machine Learning-Based Prediction of Long-Term Intraocular Pressure Fluctuations in Open-Angle Glaucoma.

OBJECTIVE: To investigate the predictability of long-term intraocular pressure (IOP) fluctuations in open-angle glaucoma eyes implanted with a telemet...