ReviewFrontiers in digital health2022
Artificial Intelligence in Predicting Systemic Parameters and Diseases From Ophthalmic Imaging.
Review in Frontiers in digital health, 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
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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
14 citing papers in PubMed, 30 citations in OpenAlex.
- Does DeepSeek Provide Clinically Acceptable Intraocular Lens (IOL) Power Predictions in Cataract Surgery? A Proof-of-Concept Study.Journal of clinical medicine · 2025Article
- Accelerated Biological Aging in Exfoliation Glaucoma Assessed by Fundus-Derived Predicted Age and Advanced Glycation End Products.International journal of molecular sciences · 2025Article
- Steroid-Responsive Intraocular Lens Deposits: A Case-Based Review of Diagnosis and Management.Cureus · 2025Review
- Fundus-Derived Predicted Age Acceleration in Glaucoma Patients Using Deep Learning and Propensity Score-Matched Controls.Journal of clinical medicine · 2025Article
- Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases.Theranostics · 2025Review
- Retina Fundus Photograph-Based Artificial Intelligence Algorithms in Medicine: A Systematic Review.Ophthalmology and therapy · 2024Review
- A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images.Frontiers in endocrinology · 2024Article
- Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives.Journal of personalized medicine · 2023Review
- Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores.European heart journal. Digital health · 2023Article
- The challenge of ocular inflammation in systemic vasculitis: How to address inequalities of care?Rheumatology and immunology research · 2023Article
- Advances in artificial intelligence models and algorithms in the field of optometry.Frontiers in cell and developmental biology · 2023Review
- Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images.Frontiers in cell and developmental biology · 2023Review
- Predicting Systemic Health Features from Retinal Fundus Images Using Transfer-Learning-Based Artificial Intelligence Models.Diagnostics (Basel, Switzerland) · 2022Article
- Applications of artificial intelligence-assisted retinal imaging in systemic diseases: A literature review.Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological SocietyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) analytics has been used to predict, classify, and aid clinical management of multiple eye diseases. Its robust performances have prompted researchers to expand the use of AI into predicting systemic, non-ocular diseases and parameters based on ocular images. Herein, we discuss the reasons why the eye is well-suited for systemic applications, and review the applications of deep learning on ophthalmic images in the prediction of demographic parameters, body composition factors, and diseases of the cardiovascular, hematological, neurodegenerative, metabolic, renal, and hepatobiliary systems. Three main imaging modalities are included-retinal fundus photographs, optical coherence tomographs and external ophthalmic images. We examine the range of systemic factors studied from ophthalmic imaging in current literature and discuss areas of future research, while acknowledging current limitations of AI systems based on ophthalmic images.
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.