Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

6,142 articles
Stay Ahead - Weekly Ophthalmology research updates
Subscribe
Browse Specialties
Showing 64-84 of 6,142 articles
Artificial Intelligence for Tumor [F]FDG PET Imaging: Advancements and Future Trends - Part II.

The integration of artificial intelligence (AI) into [F]FDG PET/CT imaging continues to expand, offe...

Diabetic retinopathy detection from fundus images: A wide survey from grading to segmentation of lesions.

Diabetes is one of the most common diseases worldwide and requires accurate diagnosis. Patients with...

Video-based pupillometry using Fourier Mellin image correlation.

We introduce a novel method for evaluating the pupil light reflex (PLR) response using digital video...

Machine learning technology in the classification of glaucoma severity using fundus photographs.

This study evaluates the performance of a machine learning model in classifying glaucoma severity us...

Enhanced Dual-Pattern Matching with Vision-Language Representation for out-of-Distribution Detection.

Out-of-distribution (OOD) detection presents a significant challenge in deploying pattern recognitio...

Synergistic fusion: An integrated pipeline of CLAHE, YOLO models, and advanced super-resolution for enhanced thermal eye detection.

Accurate eye detection in thermal images is essential for diverse applications, including biometrics...

Transcriptional modulation unique to vulnerable motor neurons predicts ALS across species and SOD1 mutations.

Amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of motor neurons (MNs) ...

Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.

BACKGROUND: Traditional ocular gaze photograph preprocessing, relying on manual cropping and head ti...

MR-Transformer: A Vision Transformer-based Deep Learning Model for Total Knee Replacement Prediction Using MRI.

Purpose To develop a transformer-based deep learning model-MR-Transformer-that leverages ImageNet p...

Collaborative Integration of AI and Human Expertise to Improve Detection of Chest Radiograph Abnormalities.

Purpose To develop a collaborative AI system that integrates eye gaze data and radiology reports to...

A Device for Computer Vision Analysis of Fungal Features Outperforms Quantitative Manual Microscopy by Experts in Discerning a Host Resistance Locus.

Accurate, quantitative phenotyping aids in the discovery of quantitative trait loci, particularly th...

Application of real-time artificial intelligence to cataract surgery.

BACKGROUND/AIMS: Artificial intelligence (AI) in Ophthalmology has yet to be applied to real-time ca...

Efficient Visual Transformer by Learnable Token Merging.

Self-attention and transformers have been widely used in deep learning. Recent efforts have been dev...

Vision-language model performance on the Japanese Nuclear Medicine Board Examination: high accuracy in text but challenges with image interpretation.

OBJECTIVE: Vision language models (VLMs) allow visual input to Large Language Models. VLMs have been...

Vision transformer and complex network analysis for autism spectrum disorder classification in T1 structural MRI.

BACKGROUND: Autism spectrum disorder (ASD) affects social interaction, communication, and behavior. ...

Dynamic modifications of circular RNAs drive oncogenesis.

Circular RNAs (circRNAs) are a class of covalently closed non-coding RNAs that regulate the progress...

VAULT-OCT: Vault Accuracy Using Deep Learning Technology - An AI Model for Predicting Implantable Collamer Lens Postoperative Vault with AS-OCT.

PURPOSE: To develop an accurate deep learning model, VAULT-OCT, to predict postoperative vault of ph...

Nurses' Insights on the Braden Scale and Their Vision for Artificial Intelligence Innovations: A Mixed Methods Study.

AIMS: This study aimed to explore nurses' experiences with the Braden Scale, assess their readiness ...

Diagnosing pathologic myopia by identifying morphologic patterns using ultra widefield images with deep learning.

Pathologic myopia is a leading cause of visual impairment and blindness. While deep learning-based a...

Browse Specialties