Ophthalmology

Application of Artificial Intelligence to Deliver Healthcare From the Eye.

IMPORTANCE: Oculomics is the science of analyzing ocular data to identify, diagnose, and manage systemic disease. This article focuses on prescreening, its use with retinal images analyzed by artificial intelligence (AI), to identify ocular or systemic disease or potential disease in asymptomatic individuals. The implementation of prescreening in a coordinated care system, defined as Healthcare Fr...

Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.

SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause of vision impairment, by identifying subtle microvascular changes.

Learning Emotion Category Representation to Detect Emotion Relations Across Languages.

Understanding human emotions is crucial for a myriad of applications, from psychological research to advancements in Natural Language Processing (NLP)...

Inter-Relationships Between the Deep Learning-Based Pachychoroid Index and Clinical Features Associated with Neovascular Age-Related Macular Degeneration.

: To investigate the impact of pachychoroid on the clinical features of neovascular age-related macular degeneration (nAMD) in Japan using the deep le...

Multimodal AI diagnostic system for neuromyelitis optica based on ultrawide-field fundus photography.

PURPOSE: While deep learning (DL) has demonstrated significant utility in ocular diseases, no clinically validated algorithm currently exists for diag...

Rapid Detection of Physicochemical Indicators of Tobacco Flavorings Using Fourier-Transform Near Infrared Spectroscopy with Chemometrics and Machine Learning.

Timely and rapid monitoring of the quality of tobacco flavorings is crucial for the accurate quality management of cigarette products. In this study, ...

AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases.

BACKGROUND: Artificial intelligence (AI) plays a promising role in ophthalmic imaging by providing innovative, non-invasive tools for the early detect...

Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.

BACKGROUND: Accurate measurement of anterior segment parameters is crucial for diagnosing and managing ophthalmic conditions, such as glaucoma, catara...

Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics.

PurposeTo identify parameters that are significant risk predictors of visual field (VF) progression in patients with ocular hypertension (OHT) or earl...

A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading.

As the most common complication of diabetes, diabetic retinopathy (DR) is one of the main causes of irreversible blindness. Automatic DR grading plays...

Frozen Large-Scale Pretrained Vision-Language Models are the Effective Foundational Backbone for Multimodal Breast Cancer Prediction.

Breast cancer is a pervasive global health concern among women. Leveraging multimodal data from enterprise patient databases-including Picture Archivi...

Assessing the effects of a 660 nm diode laser on crustacean eyes.

Sustainable management of crustacean fisheries requires accurate and timely data for population modelling, but many stocks are data deficient. To addr...

Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.

Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR...

Effects of anthropomorphic features of co-robots on users' perception and emotional responses during human-robot collaboration.

Human-robot collaboration (HRC) is growing across sectors like manufacturing and healthcare. This study explores how anthropomorphic features, specifi...

Deep learning-assisted 10-μL single droplet-based viscometry for human aqueous humor.

Probing the viscosity of human aqueous humor is crucial for optimizing micro-tube shunts in glaucoma treatment. However, conventional viscometers are ...

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients often cycle through cytotoxic chemotherapy (CC), ep...

Artificial intelligence in retinal image analysis for hypertensive retinopathy diagnosis: a comprehensive review and perspective.

Hypertensive retinopathy (HR) occurs when the choroidal vessels, which form the photosensitive layer at the back of the eye, are injured owing to high...

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.

Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools...

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF...

Enhanced glaucoma classification through advanced segmentation by integrating cup-to-disc ratio and neuro-retinal rim features.

Glaucoma is a progressive eye condition caused by high intraocular fluid pressure, damaging the optic nerve, leading to gradual, irreversible vision l...