AIMC Topic: Retinal Diseases
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The impact of artificial intelligence on retinal disease management: Vision Academy retinal expert consensus.
Current opinion in ophthalmology
Jul 13, 2023
PURPOSE OF REVIEW: The aim of this review is to define the "state-of-the-art" in artificial intelligence (AI)-enabled devices that support the management of retinal conditions and to provide Vision Academy recommendations on the topic.
Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice.
PloS one
Mar 27, 2023
AIM/BACKGROUND: To aim of this study is to develop an artificial intelligence (AI) that aids in the thought process by providing retinal clinicians with clinically meaningful or abnormal findings rather than just a final diagnosis, i.e., a "wayfindin...
Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene).
BMJ open
Mar 20, 2023
INTRODUCTION: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients ...
Enhancing retinal images in low-light conditions using semidecoupled decomposition.
Medical & biological engineering & computing
Mar 14, 2023
Eye diseases that are common and many diseases that result in visual ailments, such as diabetes and vascular disease, can be diagnosed through retinal imaging. The enhancement of retinal images often helps in diagnosing diseases related to retinal or...
Deep-learning-based AI for evaluating estimated nonperfusion areas requiring further examination in ultra-widefield fundus images.
Scientific reports
Dec 17, 2022
We herein propose a PraNet-based deep-learning model for estimating the size of non-perfusion area (NPA) in pseudo-color fundus photos from an ultra-wide-field (UWF) image. We trained the model with focal loss and weighted binary cross-entropy loss t...
Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Nov 28, 2022
PURPOSE: To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.
Systems medicine and artificial intelligence in retinal disease.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Oct 24, 2022
Temporal deep learning framework for retinopathy prediction in patients with type 1 diabetes.
Artificial intelligence in medicine
Sep 26, 2022
The adoption of electronic health records in hospitals has ensured the availability of large datasets that can be used to predict medical complications. The trajectories of patients in real-world settings are highly variable, making longitudinal data...
Multi-label classification of fundus images with graph convolutional network and LightGBM.
Computers in biology and medicine
Aug 11, 2022
Early detection and treatment of retinal disorders are critical for avoiding irreversible visual impairment. Given that patients in the clinical setting may have various types of retinal illness, the development of multi-label fundus disease detectio...
Robust Fovea Detection in Retinal OCT Imaging Using Deep Learning.
IEEE journal of biomedical and health informatics
Aug 11, 2022
The fovea centralis is an essential landmark in the retina where the photoreceptor layer is entirely composed of cones responsible for sharp, central vision. The localization of this anatomical landmark in optical coherence tomography (OCT) volumes i...
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