AIMC Topic: Retinopathy of Prematurity

Clear Filters Showing 21 to 30 of 57 articles

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Sensors (Basel, Switzerland) Dec 27, 2022
Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis and treatment are of great significance. Due to the lack of timely and effective fundus screening fo...
Humans Deep Learning Telemedicine Infant, Premature Retinopathy of Prematurity Artificial Intelligence Infant, Newborn Infant
View on PubMed DOI

Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity.

JAMA network open Jun 1, 2022
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Prediction of ROP before onset holds great promise for reducing the risk of blindness.
Deep Learning Retinopathy of Prematurity Blindness Risk Factors Male Infant Female Infant, Newborn Humans Retrospective Studies
View on PubMed DOI

Assistive Framework for Automatic Detection of All the Zones in Retinopathy of Prematurity Using Deep Learning.

Journal of digital imaging Jul 8, 2021
Retinopathy of prematurity (ROP) is a potentially blinding disorder seen in low birth weight preterm infants. In India, the burden of ROP is high, with nearly 200,000 premature infants at risk. Early detection through screening and treatment can prev...
Infant, Premature Humans Infant, Low Birth Weight Infant, Newborn Deep Learning Retinopathy of Prematurity Retina
View on PubMed DOI

Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

JAMA network open May 3, 2021
IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of RO...
Humans Male Deep Learning Area Under Curve Infant, Premature Female Infant, Newborn Sensitivity and Specificity Neonatal Screening Ophthalmoscopy Retinopathy of Prematurity
View on PubMed DOI

Key factors in a rigorous longitudinal image-based assessment of retinopathy of prematurity.

Scientific reports Mar 8, 2021
To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias and ability to detect typical progression (e.g. International Classification of Retinopathy of Prem...
Infant, Premature Ophthalmoscopy Retinopathy of Prematurity Male Image Processing, Computer-Assisted Telemedicine Female Infant, Newborn Humans Artificial Intelligence
View on PubMed DOI

Deep Learning for the Diagnosis of Stage in Retinopathy of Prematurity: Accuracy and Generalizability across Populations and Cameras.

Ophthalmology. Retina Feb 6, 2021
PURPOSE: Stage is an important feature to identify in retinal images of infants at risk of retinopathy of prematurity (ROP). The purpose of this study was to implement a convolutional neural network (CNN) for binary detection of stages 1, 2, and 3 in...
Photography North America Nepal Datasets as Topic Reference Standards Gestational Age Retinopathy of Prematurity Image Processing, Computer-Assisted Area Under Curve Birth Weight Infant, Newborn Reproducibility of Results Sensitivity and Specificity Deep Learning Humans ROC Curve Male Female Diagnosis, Computer-Assisted
View on PubMed DOI

Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale.

Ophthalmology Oct 27, 2020
PURPOSE: To evaluate the clinical usefulness of a quantitative deep learning-derived vascular severity score for retinopathy of prematurity (ROP) by assessing its correlation with clinical ROP diagnosis and by measuring clinician agreement in applyin...
Humans Algorithms Severity of Illness Index Deep Learning Retrospective Studies Infant, Newborn Retinopathy of Prematurity Retinal Vessels Follow-Up Studies Gestational Age Ophthalmoscopy
View on PubMed DOI

Automated detection of early-stage ROP using a deep convolutional neural network.

The British journal of ophthalmology Aug 23, 2020
BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).
Retinopathy of Prematurity Birth Weight Infant, Premature Infant, Low Birth Weight Humans Gestational Age Diagnosis, Computer-Assisted Neural Networks, Computer ROC Curve Image Processing, Computer-Assisted Infant, Newborn Algorithms Cross-Sectional Studies Sensitivity and Specificity Retrospective Studies Male Female
View on PubMed DOI

Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale.

Ophthalmology. Retina May 4, 2020
PURPOSE: Retinopathy of prematurity is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective, which leads to treatment differences. Our goal was to determine objective differences in the diagnosis of plus disease betw...
Gestational Age Humans Retinopathy of Prematurity Female Infant, Newborn Male Algorithms Severity of Illness Index Retrospective Studies Deep Learning
View on PubMed DOI

Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach.

Translational vision science & technology Feb 14, 2020
PURPOSE: Retinopathy of prematurity (ROP), a leading cause of childhood blindness, is diagnosed by clinical ophthalmoscopic examinations or reading retinal images. Plus disease, defined as abnormal tortuosity and dilation of the posterior retinal blo...
Retinopathy of Prematurity Child Humans Retinal Vessels Area Under Curve Neural Networks, Computer Ophthalmoscopy Infant, Newborn
View on PubMed DOI
Popular Topics
Recent Journals