Ophthalmology

Diagnostic Performance of Deep Learning Using Retinal Images for Detection of Chronic Kidney Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Multiple investigations have been conducted to diagnose chronic kidney disease (CKD) from photographs of retina using deep learning models, with a wide range of diagnostic performance, which necessitates the importance of a comprehensive review. Therefore, in this meta-analysis, we estimated the detection performance of deep learning models for the diagnosis of CKD using retinal photog...

A novel approach for liver steatosis assessment in ultrasound images using an adapted Vision-Language Foundation Model.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is among the most prevalent chronic liver diseases worldwide. B-mode ultrasound remains the first-line screening modality, yet its qualitative nature and inter-observer variability limit diagnostic consistency. Existing AI approaches largely rely on single-image classification with opaque outputs that do not reflect exam-level clinic...

Automated AI quantification of retinal parameters associated with axial length progression in children: a cohort study.

PURPOSE: This study investigated whether quantitative retinal parameters derived from colour fundus photography are associated with axial length (AL) ...

EndoVLM: A Vision-Language Assistant for Gastrointestinal Endoscopy.

Gastrointestinal endoscopy generates extensive high-resolution video data, posing significant challenges for efficient and accurate computer-aided dia...

Correction: Artificial intelligence for early detection of diabetic retinopathy: A vision transformer-based approach.

[This corrects the article DOI: 10.1371/journal.pone.0350854.].

The Importance of Artificial Intelligence in Nursing: A Fundamentals of Care Perspective.

AIM: To analyze the integration of Artificial Intelligence in nursing through the lens of the Fundamentals of Care framework. DESIGN: A discursive pap...

Research progress in the clinical application of AI in strabismus.

PURPOSE: Strabismus diagnosis and management remain subjective due to variable measurement techniques and lack of standardized surgical criteria. Arti...

Automated quantification of parafoveal microvascular complexity using deep learning-based OCTA segmentation and foveal avascular zone detection.

BACKGROUND: Quantitative analysis of retinal microvasculature from optical coherence tomography angiography (OCTA) is limited by artifacts and manual ...

Machine Learning-Based Prediction of Cycloplegic Refraction Using the Eyerobo Vision Screener: Design-A Cross-Sectional Comparative Device Study.

INTRODUCTION: A cross-sectional comparative device study to compare the Eyerobo Vision Screener (VS), a portable handheld photorefractor, against a co...

Diagnostic Accuracy of Multimodal Large Language Models in Retinal Fundus Photography.

PURPOSE: Artificial intelligence in ophthalmology has mostly used task-specific convolutional neural networks. The performance of general-purpose mult...

Research Progress of Diabetes-related Glaucoma: Mechanisms, Impacts and Management Strategies.

Diabetes mellitus (DM), a highly prevalent metabolic disorder, is increasingly recognised for its significant association with glaucoma, a leading cau...

A decade of artificial intelligence research in ophthalmology: Global trends and transferable insights for medical AI.

To characterize global trends in ophthalmic AI research from 2015-2025 and drive transferable insights into the broader evolution of AI in medicine, w...

Identification and risk-factor analysis for individuals at high risk for keratoconus via machine learning and logistic regression.

PURPOSE: To evaluate keratoconus (KC) risk factors and to develop a machine-learning (ML) model for KC and myopia classification. METHODS: In this ret...

A Risk Prediction Model for Normal-Tension Glaucoma Progression Integrating Genetic Markers and Corneal Biomechanics.

OBJECTIVE: Normal-tension glaucoma (NTG) is characterized by progressive optic nerve damage despite intraocular pressure remaining consistently within...

Uncoupling Type I Interferon Benefits From Inflammatory Toxicity: Transformer-Prioritized Precision Agonists for Potent and Safer Cancer Immunotherapy.

Paclitaxel (PTX) chemotherapy is constrained by an "immunomodulatory paradox," where antitumor Type I Interferon (IFN-I) activation is coupled with de...

A Methodological Framework for Studying Online Language-Vision Interplay in Human-Robot Interaction.

Investigating the real-time interplay between language and vision has traditionally involved a trade-off between experimental control and interactive ...

Grading-labour cost analysis of AI-assisted versus human-only diabetic retinopathy screening in two Danish healthcare settings.

PURPOSE: Diabetic retinopathy (DR) screening is essential to prevent vision loss, yet rising diabetes prevalence threatens to outpace ophthalmology ca...

Comparative Image-Based Evaluation of Deep Learning Models for the Diagnosis of Different Ocular Diseases in Cats.

Ocular pathologies are a leading cause of visual impairment in cats and require accurate, timely diagnosis for effective treatment. This study aimed t...

Deep Learning Classification and Motion-Based Analysis of Aedes aegypti Red-Eye GSS Larvae for SIT Applications.

Aedes aegypti is a major vector of arboviral diseases, including dengue, Zika, and chikungunya, posing significant global public health challenges. Ef...

Identification and localization of myopic macular neovascularization using deep learning.

PURPOSE: Myopia is rapidly increasing worldwide, with macular neovascularization (MNV) representing a major cause of vision loss. Early diagnosis rema...