Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis

R Aggarwal, V Sounderajah, G Martin, DSW Ting… - NPJ digital …, 2021 - nature.com
Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

[HTML][HTML] A review of deep learning for screening, diagnosis, and detection of glaucoma progression

AC Thompson, AA Jammal… - … vision science & …, 2020 - iovs.arvojournals.org
Because of recent advances in computing technology and the availability of large datasets,
deep learning has risen to the forefront of artificial intelligence, with performances that often …

A generalizable deep learning regression model for automated glaucoma screening from fundus images

R Hemelings, B Elen, AK Schuster, MB Blaschko… - NPJ digital …, 2023 - nature.com
A plethora of classification models for the detection of glaucoma from fundus images have
been proposed in recent years. Often trained with data from a single glaucoma clinic, they …

Detection of progressive glaucomatous optic nerve damage on fundus photographs with deep learning

FA Medeiros, AA Jammal, EB Mariottoni - Ophthalmology, 2021 - Elsevier
Purpose To investigate whether predictions of retinal nerve fiber layer (RNFL) thickness
obtained from a deep learning model applied to fundus photographs can detect progressive …

Discovery and clinical translation of novel glaucoma biomarkers

G Beykin, AM Norcia, VJ Srinivasan, A Dubra… - Progress in Retinal and …, 2021 - Elsevier
Glaucoma and other optic neuropathies are characterized by progressive dysfunction and
loss of retinal ganglion cells and their axons. Given the high prevalence of glaucoma-related …

Development and clinical deployment of a smartphone-based visual field deep learning system for glaucoma detection

F Li, D Song, H Chen, J Xiong, X Li, H Zhong… - NPJ digital …, 2020 - nature.com
Abstract By 2040,~ 100 million people will have glaucoma. To date, there are a lack of high-
efficiency glaucoma diagnostic tools based on visual fields (VFs). Herein, we develop and …

Artificial intelligence algorithms to diagnose glaucoma and detect glaucoma progression: translation to clinical practice

AS Mursch-Edlmayr, WS Ng… - … vision science & …, 2020 - tvst.arvojournals.org
Purpose: This concise review aims to explore the potential for the clinical implementation of
artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma …

Deep learning image analysis of optical coherence tomography angiography measured vessel density improves classification of healthy and glaucoma eyes

C Bowd, A Belghith, LM Zangwill, M Christopher… - American journal of …, 2022 - Elsevier
Purpose To compare convolutional neural network (CNN) analysis of en face vessel density
images to gradient boosting classifier (GBC) analysis of instrument-provided, feature-based …

Artificial intelligence and machine learning in ophthalmology: A review

O Srivastava, M Tennant, P Grewal… - Indian Journal of …, 2023 - journals.lww.com
Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has
propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical …

Artificial intelligence in ophthalmology in 2020: a technology on the cusp for translation and implementation

DV Gunasekeran, TY Wong - The Asia-Pacific Journal of …, 2020 - journals.lww.com
W ith aging populations, health systems worldwide are struggling to provide adequate eye
care at the population level, giving rise to projections of increasing levels of visual …