ArticleOphthalmology. Glaucoma
Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.
Article in Ophthalmology. Glaucoma. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Diagnostic Likelihood Ratios for Glaucoma Using Deep Learning-Predicted Retinal Nerve Fiber Layer Thickness from Fundus Photographs.Ophthalmology science · 2026Article
- Improving Generalization of Deep Learning for Glaucoma Classification Under Real-World Domain Shift via Unsupervised Domain Adaptation.Translational vision science & technology · 2026Article
- Applications of Large Language Models in Glaucoma: A Scoping Review.Vision (Basel, Switzerland) · 2026Review
- Beyond the clinic: a community-embedded, multidomain framework for early detection of glaucoma.Frontiers in public health · 2026Article
- Detection of Ocular Surface Squamous Neoplasia Using Artificial Intelligence With Anterior Segment Optical Coherence Tomography.American journal of ophthalmology · 2025Article
- Lights and Shadows on Artificial Intelligence in Glaucoma: Transforming Screening, Monitoring, and Prognosis.Journal of clinical medicine · 2025Review
- Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program [Letter].Clinical ophthalmology (Auckland, N.Z.) · 2025Article
- The value of virtual glaucoma clinics: a review.Eye (London, England) · 2024Review
- Computer-Aided Discrimination of Glaucoma Patients from Healthy Subjects Using the RETeval Portable Device.Diagnostics (Basel, Switzerland) · 2024Article
- The utilization of artificial intelligence in glaucoma: diagnosis versus screening.Frontiers in ophthalmology · 2024Review
- Classification of Color Fundus Photographs Using Fusion Extracted Features and Customized CNN Models.Healthcare (Basel, Switzerland) · 2023Article
- Medical Application of Geometric Deep Learning for the Diagnosis of Glaucoma.Translational vision science & technology · 2023Article
- Advances in artificial intelligence models and algorithms in the field of optometry.Frontiers in cell and developmental biology · 2023Review
- Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images.Frontiers in cell and developmental biology · 2023Review
- The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques.Frontiers in medicine · 2022Review
- Optic Nerve Imaging-From Disc Photos to OCT.Ophthalmology. GlaucomaReview
- A Practical Guide to Evaluating Artificial Intelligence Imaging Models in Scientific Literature.Ophthalmology scienceArticle
- Deep Learning with Disc Photos or OCT Scans in Glaucoma Detection.Ophthalmology scienceArticle
- Comparison of Deep Learning and Clinician Performance for Detecting Referable Glaucoma from Fundus Photographs in a Safety Net Population.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in the diagnosis and treatment of various ophthalmic conditions. In a session entitled "Artificial Intelligence for Glaucoma," a panel of glaucoma specialists, researchers, industry experts, and patients convened to share current research on the application of AI to commonly used diagnostic modalities, including fundus photography, OCT imaging, standard automated perimetry, and gonioscopy. The conference participants focused on the use of AI as a tool for disease prediction, highlighted its ability to address inequalities, and presented the limitations of and challenges to its clinical application. The panelists' discussion addressed AI and health equities from clinical, societal, and regulatory perspectives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.