ArticleJournal of ophthalmology2021
An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging.
Article in Journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Artificial intelligence in glaucoma: opportunities, challenges, and future directions.Biomedical engineering online · 2023Pooled it
- Pooled it
- A hybrid model for early diagnosis of ophthalmology diseases leveraging CNNs, SBOA optimization, and XAI for visualization.Physical and engineering sciences in medicine · 2026Article
- Artificial Intelligence in Glaucoma: Advances in Diagnosis, Progression Forecasting, and Surgical Outcome Prediction.International journal of molecular sciences · 2025Review
- Evaluating real-world performance of an automated offline glaucoma AI on a smartphone fundus camera across glaucoma severity stages.PloS one · 2025Article
- Automated Classification of Physiologic, Glaucomatous, and Glaucoma-Suspected Optic Discs Using Machine Learning.Diagnostics (Basel, Switzerland) · 2024Article
- Knowledge and Awareness of Glaucoma Among People Living in Taif City in the Western Region of Saudi Arabia.Cureus · 2023Article
- Agreement between Five Experts and the Laguna ONhE Automatic Colourimetric Application Interpreting the Glaucomatous Aspect of the Optic Nerve.Journal of clinical medicine · 2023Article
- An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging.Journal of ophthalmology · 2021Article
- Highly Accurate and Precise Automated Cup-to-Disc Ratio Quantification for Glaucoma Screening.Ophthalmology scienceArticle
- Application of artificial intelligence in glaucoma care: An updated review.Taiwan journal of ophthalmologyReview
- Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.Ophthalmology. GlaucomaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
resultsThe system achieved an accuracy of 89.67% (sensitivity, 83.33%; specificity, 93.89%; and AUC, 0.93). For external validation, the Retinal Fundus Image Database for Glaucoma Analysis dataset, which has 638 gradable quality images, was used. Here, the model achieved an accuracy of 83.54% (sensitivity, 80.11%; specificity, 84.96%; and AUC, 0.85).
conclusionsHaving demonstrated an accurate and fully automated glaucoma-suspect screening system that can be deployed on telemedicine platforms, we plan prospective trials to determine the feasibility of the system in primary-care settings.
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.