ReviewTurkish journal of ophthalmology2020
Artificial Intelligence and Ophthalmology
Review in Turkish journal of ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review.Eye (London, England) · 2023Pooled it
- Myopia prediction: a systematic review.Eye (London, England) · 2022Pooled it
- Accuracy and Effectiveness of AI-Powered Systems in Patient Counseling, Education, and Management in Optometry and Related Eye-Care Settings: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Advancements in AI-based quantitative analysis of fundus tessellation and its application in myopia research.Frontiers in medicine · 2026Review
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Artificial Intelligence in Ophthalmology: Practical Applications, Subspecialty Evidence and Real-World Deployment.Cureus · 2025Review
- A Narrative Review of Ethical Issues in the Use of Artificial Intelligence Enabled Diagnostics for Diabetic Retinopathy.Journal of evaluation in clinical practice · 2025Review
- Performance of ChatGPT-4 Omni and Gemini 1.5 Pro on Ophthalmology-Related Questions in the Turkish Medical Specialty Exam.Turkish journal of ophthalmology · 2025Article
- Review
- Artificial intelligence virtual assistants in primary eye care practice.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- Clinical performance of an interactive platform based on artificial intelligence in ophthalmology: experience in a third-level reference center.Frontiers in medicine · 2025Article
- An Overview on the Effects of Some Carotenoids on Health: Lutein and Zeaxanthin.Current nutrition reports · 2024Review
- Artificial Intelligence in Medical Metaverse: Applications, Challenges, and Future Prospects.Current medical science · 2024Review
- Application of AI-empowered scenario-based simulation teaching mode in cardiovascular disease education.BMC medical education · 2024Article
- Self-supervised contrastive learning improves machine learning discrimination of full thickness macular holes from epiretinal membranes in retinal OCT scans.PLOS digital health · 2024Article
- Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.Updates in surgery · 2024Review
- ChatGPT and Beyond: An overview of the growing field of large language models and their use in ophthalmology.Eye (London, England) · 2024Review
- Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.Translational vision science & technology · 2024Article
- Macular edema in retinal fundus images by a computational algorithmRevista medica del Instituto Mexicano del Seguro Social · 2024Article
- Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging.Frontiers in bioengineering and biotechnology · 2024Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence is advancing rapidly and making its way into all areas of our lives. This review discusses developments and potential practices regarding the use of artificial intelligence in the field of ophthalmology, and the related topic of medical ethics. Various artificial intelligence applications related to the diagnosis of eye diseases were researched in books, journals, search engines, print and social media. Resources were cross-checked to verify the information. Artificial intelligence algorithms, some of which were approved by the US Food and Drug Administration, have been adopted in the field of ophthalmology, especially in diagnostic studies. Studies are being conducted that prove that artificial intelligence algorithms can be used in the field of ophthalmology, especially in diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity. Some of these algorithms have come to the approval stage. The current point in artificial intelligence studies shows that this technology has advanced considerably and shows promise for future work. It is believed that artificial intelligence applications will be effective in identifying patients with preventable vision loss and directing them to physicians, especially in developing countries where there are fewer trained professionals and physicians are difficult to reach. When we consider the possibility that some future artificial intelligence systems may be candidates for moral/ethical status, certain ethical issues arise. Questions about moral/ethical status are important in some areas of applied ethics. Although it is accepted that current intelligence systems do not have moral/ethical status, it has yet to be determined what the exact the characteristics that confer moral/ethical status are or will be.
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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.