AIMC Topic: Ophthalmoscopy
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Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity.
Ophthalmology
Jun 10, 2024
PURPOSE: To evaluate whether providing clinicians with an artificial intelligence (AI)-based vascular severity score (VSS) improves consistency in the diagnosis of plus disease in retinopathy of prematurity (ROP).
Smartphone Eye Examination: Artificial Intelligence and Telemedicine.
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Aug 16, 2023
The current medical scenario is closely linked to recent progress in telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye examination may represent a promising tool in the technological spectrum, with special inte...
[Ocular changes as a diagnostic tool for malaria].
Die Ophthalmologie
Dec 23, 2021
BACKGROUND: According to the WHO Malaria Report 2019 a total of 229 million people fall ill with malaria each year and two thirds of deaths involve children under 5 years of age.
Artificial intelligence-based detection of epimacular membrane from color fundus photographs.
Scientific reports
Sep 29, 2021
Epiretinal membrane (ERM) is a common ophthalmological disorder of high prevalence. Its symptoms include metamorphopsia, blurred vision, and decreased visual acuity. Early diagnosis and timely treatment of ERM is crucial to preventing vision loss. Al...
An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning.
Computational and mathematical methods in medicine
May 31, 2021
Diabetic retinopathy occurs as a result of the harmful effects of diabetes on the eyes. Diabetic retinopathy is also a disease that should be diagnosed early. If not treated early, vision loss may occur. It is estimated that one third of more than ha...
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...
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...
Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis.
Ophthalmology. Retina
Feb 1, 2021
PURPOSE: To develop a deep learning (DL) system that can detect referable diabetic retinopathy (RDR) and vision-threatening diabetic retinopathy (VTDR) from images obtained on ultra-widefield scanning laser ophthalmoscope (UWF-SLO).
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...
AMD-GAN: Attention encoder and multi-branch structure based generative adversarial networks for fundus disease detection from scanning laser ophthalmoscopy images.
Neural networks : the official journal of the International Neural Network Society
Sep 17, 2020
The scanning laser ophthalmoscopy (SLO) has become an important tool for the determination of peripheral retinal pathology, in recent years. However, the collected SLO images are easily interfered by the eyelash and frame of the devices, which heavil...
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