ReviewDisease markers2022
Research Progress of Artificial Intelligence Image Analysis in Systemic Disease-Related Ophthalmopathy.
Review in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Ophthalmology specialty training for general practitioners in China: current status and the Shenzhen model.BMC primary care · 2026Observational
- Associations between quantitative ocular surface features and CT morphology of the levator palpebrae superioris complex in patients with thyroid eye disease and upper eyelid retraction: a cross-sectional study.Frontiers in medicine · 2026Article
- Advancements and challenges of ultrasound imaging in the management of thyroid-associated ophthalmopathy.World journal of radiology · 2025Review
- Application of artificial intelligence in myopia prevention and control.Pediatric investigation · 2025Review
- The Future of Breast Cancer Organized Screening Program Through Artificial Intelligence: A Scoping Review.Healthcare (Basel, Switzerland) · 2025Review
- A scoping review of advancements in machine learning for glaucoma: current trends and future direction.Frontiers in medicine · 2025Article
- MSLI-Net: retinal disease detection network based on multi-segment localization and multi-scale interaction.Frontiers in cell and developmental biology · 2025Article
- Bibliometric analysis of hotspots and trends of global myopia research.International journal of ophthalmology · 2024Article
- Advances in artificial intelligence in thyroid-associated ophthalmopathy.Frontiers in endocrinology · 2024Review
- Exploring the effect of gestational diabetes mellitus on retinal vascular morphology by PKSEA-Net.Frontiers in cell and developmental biology · 2024Article
- Automatic measurement of exophthalmos based orbital CT images using deep learning.Frontiers in cell and developmental biology · 2023Article
- Research progress in artificial intelligence assisted diabetic retinopathy diagnosis.International journal of ophthalmology · 2023Article
- Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images.Frontiers in cell and developmental biology · 2023Review
- Advances in artificial intelligence models and algorithms in the field of optometry.Frontiers in cell and developmental biology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The eye is one of the most important organs of the human body. Eye diseases are closely related to other systemic diseases, both of which influence each other. Numerous systemic diseases lead to special clinical manifestations and complications in the eyes. Typical diseases include diabetic retinopathy, hypertensive retinopathy, thyroid associated ophthalmopathy, optic neuromyelitis, and Behcet's disease. Systemic disease-related ophthalmopathy is usually a chronic disease, and the analysis of imaging markers is helpful for a comprehensive diagnosis of these diseases. Recently, artificial intelligence (AI) technology based on deep learning has rapidly developed, leading to numerous achievements and arousing widespread concern. Presently, AI technology has made significant progress in research on imaging markers of systemic disease-related ophthalmopathy; however, there are also many limitations and challenges. This article reviews the research achievements, limitations, and future prospects of AI image analysis technology in systemic disease-related ophthalmopathy.
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.