ReviewFrontiers in cell and developmental biology2023
Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images.
Review in Frontiers in cell and developmental biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Artificial intelligence in refractive surgery: progress, challenges, and future directions.Frontiers in cell and developmental biology · 2026Review
- Reconstruction of three-dimensional retinal shape from refractive topography data.Scientific reports · 2025Article
- Effective Integration of Artificial Intelligence and Blockchain Technologies for Empowerment of Drug Discovery and Development.Current drug discovery technologies · 2025Review
- Orally administered fluorescein angiography for ultra-wide-field imaging: is a safe and effective modality across different age groups and fundus diseases?Frontiers in cell and developmental biology · 2025Article
- Study of Macular Microvascular Changes in Patients with Symptomatic Lacunar Cerebral Infarction Using Viaoptical Coherence Tomography Angiography (OCTA).International journal of general medicine · 2025Article
- Artificial intelligence in ophthalmology: opportunities, challenges, and ethical considerations.Medical hypothesis, discovery & innovation ophthalmology journal · 2025Review
- Molecular and Cellular Mechanisms Involved in the Pathophysiology of Retinal Vascular Disease-Interplay Between Inflammation and Oxidative Stress.International journal of molecular sciences · 2024Review
- Retinal Vein Occlusion-Background Knowledge and Foreground Knowledge Prospects-A Review.Journal of clinical medicine · 2024Review
- Application and progress of artificial intelligence technology in the segmentation of hyperreflective foci in OCT images for ophthalmic disease research.International journal of ophthalmology · 2024Review
- Intelligent diagnosis of retinal vein occlusion based on color fundus photographs.International journal of ophthalmology · 2024Article
- Multi-Layer Preprocessing and U-Net with Residual Attention Block for Retinal Blood Vessel Segmentation.Diagnostics (Basel, Switzerland) · 2023Article
- Attention-guided cascaded network with pixel-importance-balance loss for retinal vessel segmentation.Frontiers in cell and developmental biology · 2023Article
- Multimodal data-driven approaches in retinal vein occlusion: A narrative review integrating machine learning and bioinformatics.Advances in ophthalmology practice and researchReview
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the only blood vessels that can directly be seen in the whole body, pathological changes in retinal vessels are related to the metabolic state of the whole body and many systems, which seriously affect the vision and quality of life of patients. Timely diagnosis and treatment are key to improving vision prognosis. In recent years, with the rapid development of artificial intelligence, the application of artificial intelligence in ophthalmology has become increasingly extensive and in-depth, especially in the field of retinal vascular diseases. Research study results based on artificial intelligence and fundus images are remarkable and provides a great possibility for early diagnosis and treatment. This paper reviews the recent research progress on artificial intelligence in retinal vascular diseases (including diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, retinopathy of prematurity, and age-related macular degeneration). The limitations and challenges of the research process are also discussed.
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