ArticleEye (London, England)2019
A renaissance of teleophthalmology through artificial intelligence.
Article in Eye (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Tele-ophthalmology-enabled and artificial intelligence-ready referral pathway for community optometry referrals of retinal disease: HERMES cluster randomised trial with a diagnostic accuracy study.Health technology assessment (Winchester, England) · 2025Trial
- Rerouting Eye Care: How AI and Telemedicine Are Reshaping Ophthalmology Patient Journeys in the United Kingdom and Germany.Journal of medical Internet research · 2026Article
- Dual-Branch Network with Hybrid Attention for Multimodal Ophthalmic Diagnosis.Bioengineering (Basel, Switzerland) · 2025Article
- Teleophthalmology and retina: a review of current tools, pathways and services.International journal of retina and vitreous · 2023Review
- Article
- Protocol for a systematic review and meta-analysis of the diagnostic accuracy of artificial intelligence for grading of ophthalmology imaging modalities.Diagnostic and prognostic research · 2022Article
- Artificial Intelligence and Statistics: Just the Old Wine in New Wineskins?Frontiers in digital health · 2022Article
- Teleophthalmology and Artificial Intelligence As Game Changers in Ophthalmic Care After the COVID-19 Pandemic.Cureus · 2021Review
- Impact of Artificial Intelligence on Medical Education in Ophthalmology.Translational vision science & technology · 2021Article
- Retinal vascular occlusions.Lancet (London, England) · 2020Review
- Oculoplastic video-based telemedicine consultations: Covid-19 and beyond.Eye (London, England) · 2020Article
- Deep learning for identification of peripheral retinal degeneration using ultra-wide-field fundus images: is it sufficient for clinical translation?Annals of translational medicine · 2020Article
- Commentary: Artificial intelligence - A game changer.Indian journal of ophthalmology · 2020Article
- Scaling Up Teleophthalmology for Diabetic Eye Screening: Opportunities for Widespread Implementation in the USA.Current diabetes reports · 2019Review
- Incidence of Referable Retinal Disease in Diabetic Patients at a Primary Care Practice.Journal of vitreoretinal diseasesArticle
- American Society of Retina Specialists Artificial Intelligence Task Force Report.Journal of vitreoretinal diseasesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.