ReviewEye and vision (London, England)2024
Potential applications of artificial intelligence in image analysis in cornea diseases: a review.
Review in Eye and vision (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Current Applications of Artificial Intelligence for Fuchs Endothelial Corneal Dystrophy: A Systematic Review.Translational vision science & technology · 2025Pooled it
- From Morphology to Biomarkers: Optical Coherence Tomography in Corneal Disease.Diseases (Basel, Switzerland) · 2026Review
- A Mixture-of-Experts Network for Infectious Keratitis Classification Using Multimodal Slit-Lamp Images: A Multicenter Study.Translational vision science & technology · 2026Article
- Emerging Technologies in Corneal Nerve Evaluation for Dry Eye and Ocular Surface Disease: A Review.Journal of clinical medicine · 2026Review
- Artificial intelligence in corneal endothelial disease and endothelial keratoplasty: current evidence, clinical readiness, and future directions.Frontiers in ophthalmology · 2026Review
- Deep Learning Analysis of Widefield Cornea Endothelial Imaging in Fuchs Dystrophy.Ophthalmology science · 2026Article
- The Future of Interventional Keratoconus Management: Perspectives on Integrating Epithelium-on Oxygen-Enriched Cross-Linking into Comprehensive Care Pathways.Therapeutics and clinical risk management · 2026Article
- Artificial Intelligence Application in Cornea and External Diseases.Diagnostics (Basel, Switzerland) · 2025Review
- Article
- Article
- Deep learning-based keratoconus detection from Scheimpflug images.Biomedical optics express · 2025Article
- Artificial Intelligence Applications in Ophthalmology.JMA journal · 2025Review
- Strategies for Early Keratoconus Diagnosis: A Narrative Review of Evaluating Affordable and Effective Detection Techniques.Journal of clinical medicine · 2025Review
- AI-driven strategies for advancing corneal cell therapy: a promising frontier.Frontiers in medicine · 2025Review
- Deep learning-assisted widefield endothelial imaging in Descemet membrane endothelial keratoplasty.Frontiers in medicine · 2025Article
- Anterior Segment Optical Coherence Tomography Angiography: A Review of Applications for the Cornea and Ocular Surface.Medicina (Kaunas, Lithuania) · 2024Review
- Review
- Keratoconus: imaging modalities and management.Medical hypothesis, discovery & innovation ophthalmology journal · 2024Review
- Artificial Intelligence in Clinical Diagnosis and Treatment of Dry Eye: Workflows, Effectiveness, and Evaluation.Journal of current ophthalmologyReview
- Utility of multimodal imaging in the clinical diagnosis of inherited retinal degenerations.Taiwan journal of ophthalmologyReview
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.
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.