Ophthalmology

Advances in the application of artificial intelligence-driven multi-modal imaging technologies in the comprehensive diagnosis and treatment of diabetic foot ulcers.

Diabetic foot ulcers are serious skin wounds that affect many people with diabetes, often leading to severe infections or even the loss of a limb. This paper explores how artificial intelligence -computer programs that can learn from data-is changing the way doctors find and treat these wounds. By reviewing 68 recent studies, we looked at how these smart technologies analyze different types of med...

A hierarchical transformer-graph framework for explainable student engagement estimation in E-learning videos.

The importance of understanding student engagement in learning with AI technologies is particularly relevant for the case of adaptive learning. Most current vision-based methods rely solely on appearance-based emotion detection using facial expressions. They do not consider the geometric and behavioral temporal dynamics that can occur in unconstrained webcam streaming. The main contribution of thi...

Element-to-mineral-properties conversion (EMPC) via MARSpline for 3D geometallurgical modeling of the Koashva Apatite-Nepheline Deposit, Kola Peninsula, Russia.

Efficient processing of complex ores is often hampered by an incomplete understanding of the spatial distribution of critical mineralogical properties...

Optimizing material and process parameters in laser engineered net shaping using liquid neural networks.

This study introduces a physics-based Liquid Neural Network (LNN) framework for optimization of material and process parameters in Laser Engineered Ne...

UveAI: clinic-ready scoring of retinal inflammation in uveitis on widefield fluorescein angiography using AI.

Retinal inflammation is a key determinant of visual prognosis in uveitis, yet its assessment on fluorescein angiography remains subjective, labor-inte...

Bladder cancer segmentation using u-net-based deep-learning.

We are developing a decision support system for treatment response assessment of bladder cancer by analyzing patients' CT urography (CTU) examinations...

Comparing the Use of Measured and Smoothed Data in Forecasting Visual Field Tests Using Deep Learning.

OBJECTIVE: To evaluate the impact of training and testing deep learning (DL) models for visual field (VF) forecasting using input-target pairs in whic...

AI for Relational Reconnection and Social Support in Alzheimer's Disease: A Conceptual Framework for Socially Embedded Systems.

Alzheimer's Disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques ...

Peripheral retinal haemorrhage density on ultra-widefield imaging as a novel biomarker for predicting diabetic retinopathy progression: a 2-year longitudinal study in Asians.

AIMS: To evaluate whether predominantly peripheral lesions (PPLs) and other imaging biomarkers on ultra-widefield (UWF) photography can predict the pr...

Hybrid vision-IMU deep learning framework with graph convolutional networks and attention for personalized yoga posture identification.

Asanas, are very crucial for maintaining humans physical and mental health in an efficient manner. Digital training platforms, fitness monitors, and m...

NerveAI- a machine learning algorithm for detection of nerve pain in the head and neck.

Nerve pain screening in patients with headache disorders requires specialized clinical knowledge that is frequently not readily accessible at the init...

Bridging Therapeutics and Nanotechnology in Dry Eye Disease: A Review of Risk Factors, Drug Delivery Barriers, and Recent and Future Endeavors for Disease Management.

Dry eye disease (DED) is a multifactorial ocular disorder with high prevalence among global population, characterized by tear film instability, hypero...

Machine learning-based prediction of diabetic retinopathy using clinlabomics: a multi-center study.

BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision loss, yet conventional retinal screening remains costly and resource-intensive. Thi...

The conditional indirect effect of perceived robot threat on employees' proactive behavior: the moderating role of human-robot interaction.

In the era of artificial intelligence, an increasing number of robots are entering the workplace as active contributors to organizational tasks. While...

From Tarsal Anatomy to Tear-Film Homeostasis: A History-Informed Review of the Meibomian Gland in Ocular Surface Biology.

The meibomian gland was anatomically described in 1666, but its central role in ocular surface disease emerged only after tear-film physiology, in viv...

AI-Based Automation for Medication Reconciliation: Scoping Review.

BACKGROUND: Medication reconciliation (MedRec) has the potential to improve patient safety by enhancing the continuity of medication information acros...

The potential role of artificial intelligence in the diagnosis of Acanthamoeba keratitis-a scoping review.

BACKGROUND: Acanthamoeba keratitis (AK) is a severe, sight-threatening infectious disease with a rising global incidence, linked to the increasing use...

[Chinese expert consensus on the standardized application of generative artificial intelligence large models in ophthalmology (2026)].

With the rapid development of generative artificial intelligence (AI) technologies and large AI models, these technologies are expected to play an imp...

[Artificial intelligence in pediatric ophthalmology: applications and perspectives].

Pediatric visual health is not only inextricably linked to an individual's lifelong cognitive development and quality of life, but also constitutes a ...

LiteFeatNet: A parameter-efficient and performance-centric deep learning model for multi-ocular disease identification using intermediate feature reduction from fundus images.

Convolutional Neural Networks (CNNs) require a larger amount of input samples and computing resources to learn discriminative features for accurate id...