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Journal of the American Medical Association (JAMA), 2016 Importance Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly.
Varun Gulshan +14 more
semanticscholar +1 more source
Ultrastructure of neurovascular changes in human diabetic retinopathy [PDF]
, 2018 The previous concept regarding diabetic retinopathy assigned a primary role to hyperglycemia-induced microvascular alterations, while neuronal and glial abnormalities were considered to be secondary to either ischemia or exudation.
Artico, Marco +9 more
core +1 more source
Global Prevalence and Major Risk Factors of Diabetic Retinopathy
Diabetes Care, 2012 OBJECTIVE To examine the global prevalence and major risk factors for diabetic retinopathy (DR) and vision-threatening diabetic retinopathy (VTDR) among people with diabetes. RESEARCH DESIGN AND METHODS A pooled analysis using individual participant data
J. Yau +35 more
semanticscholar +1 more source
Diabetic retinopathy detection and classification using capsule networks
Complex & Intelligent Systems, 2021 Nowadays, diabetic retinopathy is a prominent reason for blindness among the people who suffer from diabetes. Early and timely detection of this problem is critical for a good prognosis.
G. Kalyani +3 more
semanticscholar +1 more source
MicroRNAs as biomarkers of diabetic retinopathy and disease progression
Neural Regeneration Research, 2019 Diabetes mellitus, together with its complications, has been increasing in prevalence worldwide. Its complications include cardiovascular disease (e.g., myocardial infarction, stroke), neuropathy, nephropathy, and eye complications (e.g., glaucoma ...
Bridget Martinez, Philip V Peplow
doaj +1 more source
Delay in diabetic retinopathy screening increases the rate of detection of referable diabetic retinopathy [PDF]
, 2013 Aims - To assess whether there is a relationship between delay in retinopathy screening after diagnosis of Type 2 diabetes and level of retinopathy detected.
Aldington, S. J. +2 more
core +1 more source
JAMA Network Open, 2021 Key Points Question How does an artificial intelligence (AI) system for autonomous detection of vision-threatening diabetic retinopathy (vtDR) and more than mild diabetic retinopathy (mtmDR) compare with the reading center clinical reference standard ...
E. Ipp +12 more
semanticscholar +1 more source
Journal of Clinical and Translational Science, 2018 OBJECTIVES/SPECIFIC AIMS: Diabetic retinopathy is the leading cause of blindness in adults aged 25–64 years. The prevalence of diabetic retinopathy is projected to increase 4-fold by 2050. Racial and ethnic minorities have a higher prevalence and greater
Kristen Nwanyanwu +3 more
doaj +1 more source
Spatial distribution of early red lesions is a risk factor for development of vision-threatening diabetic retinopathy [PDF]
, 2017 Aims/hypothesis Diabetic retinopathy is characterised by morphological lesions related to disturbances in retinal blood flow. It has previously been shown that the early development of retinal lesions temporal to the fovea may predict the development of
A Hunter +28 more
core +3 more sources
Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images
Scientific Reports, 2021 Visually impaired and blind people due to diabetic retinopathy were 2.6 million in 2015 and estimated to be 3.2 million in 2020 globally. Though the incidence of diabetic retinopathy is expected to decrease for high-income countries, detection and ...
Kangrok Oh +5 more
semanticscholar +1 more source