ReviewFrontiers in endocrinology2024
Advances in artificial intelligence in thyroid-associated ophthalmopathy.
Review in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed.
- An explainable machine learning framework for accurate prediction of postoperative anterior chamber depth in highly myopic cataract surgery.Frontiers in cell and developmental biology · 2026Article
- Bibliometrics in thyroid eye disease.Journal of endocrinological investigation · 2026Article
- AI-based assessment of Clinical Activity Score and detection of active thyroid eye disease using facial images: validation of Glandy CAS.BMJ open ophthalmology · 2025Article
- Assessment of retinal and choroidal microcirculatory alterations following radiofrequency catheter ablation in atrial fibrillation patients using swept-source optical coherence tomography angiography.Frontiers in cell and developmental biology · 2025Article
- Comparative performance of large language models for patient-initiated ophthalmology consultations.Frontiers in public health · 2025Article
- A Comprehensive Review of Thyroid Eye Disease Pathogenesis: From Immune Dysregulations to Novel Diagnostic and Therapeutic Approaches.International journal of molecular sciences · 2024Review
- Thyroid gland dysfunction and keratoconus.Medical hypothesis, discovery & innovation ophthalmology journal · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thyroid-associated ophthalmopathy (TAO), also referred to as Graves' ophthalmopathy, is a medical condition wherein ocular complications arise due to autoimmune thyroid illness. The diagnosis of TAO, reliant on imaging, typical ocular symptoms, and abnormalities in thyroid function or thyroid-associated antibodies, is generally graded and staged. In recent years, Artificial intelligence(AI), particularly deep learning(DL) technology, has gained widespread use in the diagnosis and treatment of ophthalmic diseases. This paper presents a discussion on specific studies involving AI, specifically DL, in the context of TAO, highlighting their applications in TAO diagnosis, staging, grading, and treatment decisions. Additionally, it addresses certain limitations in AI research on TAO and potential future directions for the field.
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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.