ReviewIndian journal of ophthalmology2023
Artificial intelligence and machine learning in ophthalmology: A review.
Review in Indian journal of ophthalmology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed.
- Development of a multimodal large language model for early warning and diagnosis of chronic ocular GVHD.NPJ digital medicine · 2026Article
- Topo-CNN: Retinal Image Analysis with Topological Deep Learning.Journal of imaging informatics in medicine · 2026Article
- HOG-CNN: Integrating Histogram of Oriented Gradients with Convolutional Neural Networks for Retinal Image Classification.Journal of imaging informatics in medicine · 2026Article
- Shifting the retinal foundation models paradigm from slices to volumes for optical coherence tomography.NPJ digital medicine · 2026Article
- A refractive error prediction model for children and adolescents based on ocular biometric parameters.BMC ophthalmology · 2026Observational
- Artificial intelligence-based apps for screening and diagnosing diabetic retinopathy and common ocular disorders.World journal of methodology · 2025Review
- Article
- International corneal and ocular surface disease dataset for electronic health records.The British journal of ophthalmology · 2025Article
- Decision Tree Modeling to Predict Myopia Progression in Children Treated with Atropine: Toward Precision Ophthalmology.Diagnostics (Basel, Switzerland) · 2025Article
- Classification of ocular surface diseases: Deep learning for distinguishing ocular surface squamous neoplasia from pterygium.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Machine learning-based progress prediction in accelerated cross-linking for Keratoconus.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Innovative approaches to treatment of eye diseases: advances in stem cell therapy use in ophthalmology.International ophthalmology · 2025Review
- Lights and Shadows on Artificial Intelligence in Glaucoma: Transforming Screening, Monitoring, and Prognosis.Journal of clinical medicine · 2025Review
- Artificial intelligence virtual assistants in primary eye care practice.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- Artificial Intelligence Applications in Ophthalmology.JMA journal · 2025Review
- Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study.International journal of retina and vitreous · 2025Article
- Conjunctival Bulbar Redness Extraction Pipeline for High-Resolution Ocular Surface Photography.Translational vision science & technology · 2025Article
- Tackling visual impairment: emerging avenues in ophthalmology.Frontiers in medicine · 2025Review
- Evaluating the Application of Artificial Intelligence and Ambient Listening to Generate Medical Notes in Vitreoretinal Clinic Encounters.Clinical ophthalmology (Auckland, N.Z.) · 2025Article
- A Beginner's Guide to Artificial Intelligence for Ophthalmologists.Ophthalmology and therapy · 2024Review
Corrections and comments
- AssociatedPublication
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implications on every subspecialty within medicine. This review highlights the applications of AI in ophthalmology: a specialty that lends itself well to the integration of computer algorithms due to the high volume of digital imaging, data, and objective metrics such as central retinal thickness. The focus of this review is the use of AI in retina, cornea, anterior segment, and pediatrics.
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.