ReviewDiagnostics (Basel, Switzerland)2022
Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
What it found
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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, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature.Frontiers in medicine · 2025Pooled it
- Artificial Intelligence for Predicting Postoperative Outcomes in Anterior Segment and Ocular Adnexa Surgery: A Systematic Review.Ophthalmology science · 2026Review
- Future visual field prediction in glaucoma: an application of first-order autoregressive approach.International ophthalmology · 2026Article
- Standards for vision science librarians: 2026 review and revisions.Journal of the Medical Library Association : JMLA · 2026Review
- Neural Vision Restoration in Ophthalmology.Annals of biomedical engineering · 2026Review
- Deep Learning-Based Diagnosis of Corneal Condition by Using Raw Optical Coherence Tomography Data.Diagnostics (Basel, Switzerland) · 2025Article
- Development of a Neural Network to Predict Optimal IOP Reduction in Glaucoma Management.Vision (Basel, Switzerland) · 2025Article
- Hybrid attention-based deep learning for multi-label ophthalmic disease detection on fundus images.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Efdamrofusp alfa: an insight into the novel drug and its use in age-related macular degeneration.International journal of retina and vitreous · 2025Review
- Review
- The Role of Artificial Intelligence in Predicting the Progression of Intraocular Hypertension to Glaucoma.Life (Basel, Switzerland) · 2025Article
- Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.Ophthalmic genetics · 2025Article
- Artificial Intelligence Applications in Ophthalmology.JMA journal · 2025Review
- Review
- Article
- Effective Integration of Artificial Intelligence and Blockchain Technologies for Empowerment of Drug Discovery and Development.Current drug discovery technologies · 2025Review
- Clinical performance of an interactive platform based on artificial intelligence in ophthalmology: experience in a third-level reference center.Frontiers in medicine · 2025Article
- AI-assisted automated interpretation of corneal topography in orthokeratology patients: enhancing diagnostic precision and efficiency.International journal of ophthalmology · 2025Article
- Artificial intelligence for posterior capsule opacification.Frontiers in medicine · 2025Review
- Artificial intelligence chatbot interpretation of ophthalmic multimodal imaging cases.Eye (London, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHaving several applications in medicine, and in ophthalmology in particular, artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing a key role in diagnosing eye diseases and in predicting the evolution of these common and disabling diseases. AI tools, i.e., artificial neural networks (ANNs), are progressively involved in detecting and customized control of ophthalmic diseases. The studies that refer to the efficiency of AI in medicine and especially in ophthalmology were analyzed in this review. MATERIALS AND
methodsWe conducted a comprehensive review in order to collect all accounts published between 2015 and 2022 that refer to these applications of AI in medicine and especially in ophthalmology. Neural networks have a major role in establishing the demand to initiate preliminary anti-glaucoma therapy to stop the advance of the disease.
resultsDifferent surveys in the literature review show the remarkable benefit of these AI tools in ophthalmology in evaluating the visual field, optic nerve, and retinal nerve fiber layer, thus ensuring a higher precision in detecting advances in glaucoma and retinal shifts in diabetes. We thus identified 1762 applications of artificial intelligence in ophthalmology: review articles and research articles (301 pub med, 144 scopus, 445 web of science, 872 science direct). Of these, we analyzed 70 articles and review papers (diabetic retinopathy (N = 24), glaucoma (N = 24), DMLV (N = 15), other pathologies (N = 7)) after applying the inclusion and exclusion criteria.
conclusionIn medicine, AI tools are used in surgery, radiology, gynecology, oncology, etc., in making a diagnosis, predicting the evolution of a disease, and assessing the prognosis in patients with oncological pathologies. In ophthalmology, AI potentially increases the patient's access to screening/clinical diagnosis and decreases healthcare costs, mainly when there is a high risk of disease or communities face financial shortages. AI/DL (deep learning) algorithms using both OCT and FO images will change image analysis techniques and methodologies. Optimizing these (combined) technologies will accelerate progress in this area.
Indexed as
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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.