Artificial intelligence and deep learning in ophthalmology

DSW Ting, LR Pasquale, L Peng… - British Journal of …, 2019 - bjo.bmj.com
Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global
interest in recent years. DL has been widely adopted in image recognition, speech …

Deep learning in ophthalmology: the technical and clinical considerations

DSW Ting, L Peng, AV Varadarajan, PA Keane… - Progress in retinal and …, 2019 - Elsevier
The advent of computer graphic processing units, improvement in mathematical models and
availability of big data has allowed artificial intelligence (AI) using machine learning (ML) …

[HTML][HTML] Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices

MD Abràmoff, PT Lavin, M Birch, N Shah… - NPJ digital medicine, 2018 - nature.com
Artificial Intelligence (AI) has long promised to increase healthcare affordability, quality and
accessibility but FDA, until recently, had never authorized an autonomous AI diagnostic …

Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with …

DSW Ting, CYL Cheung, G Lim, GSW Tan, ND Quang… - Jama, 2017 - jamanetwork.com
Importance A deep learning system (DLS) is a machine learning technology with potential
for screening diabetic retinopathy and related eye diseases. Objective To evaluate the …

[HTML][HTML] Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning

MD Abràmoff, Y Lou, A Erginay… - … & visual science, 2016 - jov.arvojournals.org
Purpose: To compare performance of a deep-learning enhanced algorithm for automated
detection of diabetic retinopathy (DR), to the previously published performance of that …

Convolutional neural network for multi-class classification of diabetic eye disease

R Sarki, K Ahmed, H Wang, Y Zhang… - … Transactions on Scalable …, 2021 - vuir.vu.edu.au
Prompt examination increases the chances of effective treatment of Diabetic Eye Disease
(DED) and reduces the likelihood of permanent deterioration of vision. A key tool commonly …

[HTML][HTML] Automated detection of diabetic retinopathy using deep learning

C Lam, D Yi, M Guo, T Lindsey - AMIA summits on translational …, 2018 - ncbi.nlm.nih.gov
Diabetic retinopathy is a leading cause of blindness among working-age adults. Early
detection of this condition is critical for good prognosis. In this paper, we demonstrate the …

Automated detection of mild and multi-class diabetic eye diseases using deep learning

R Sarki, K Ahmed, H Wang, Y Zhang - Health Information Science and …, 2020 - Springer
Diabetic eye disease is a collection of ocular problems that affect patients with diabetes.
Thus, timely screening enhances the chances of timely treatment and prevents permanent …

Zoom-in-net: Deep mining lesions for diabetic retinopathy detection

Z Wang, Y Yin, J Shi, W Fang, H Li, X Wang - Medical Image Computing …, 2017 - Springer
We propose a convolution neural network based algorithm for simultaneously diagnosing
diabetic retinopathy and highlighting suspicious regions. Our contributions are two folds:(1) …

Validation of automated screening for referable diabetic retinopathy with the IDx‐DR device in the Hoorn Diabetes Care System

AA Van Der Heijden, MD Abramoff… - Acta …, 2018 - Wiley Online Library
Purpose To increase the efficiency of retinal image grading, algorithms for automated
grading have been developed, such as the IDx‐DR 2.0 device. We aimed to determine the …