ReviewOphthalmology and therapy2025
A Systematic Review of Advances in AI-Assisted Analysis of Fundus Fluorescein Angiography (FFA) Images: From Detection to Report Generation.
Review in Ophthalmology and therapy, 2025. 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.
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Who cites it
14 citing papers in PubMed.
- FFA-SegGPT: A Two-Stage Cross-Modal AI System to Optimize the Clinical Workflow of Diabetic Retinopathy FFA Interpretation.Translational vision science & technology · 2026Article
- Review
- Fundus to fluorescein angiography video generation as a retinal generative foundation model.NPJ digital medicine · 2026Article
- Improved method for optical coherence tomography angiography: from reconstruction to clinical indicator quantification.Journal of biomedical optics · 2026Article
- Review
- Integrating AI, imaging innovations and omics for precision medicine.BMJ open ophthalmology · 2026Article
- DiFFA: A Diffusion-Based Model for Synthetic Fundus Fluorescein Angiography to Enhance Detection of Diabetic Microvascular Complication.Translational vision science & technology · 2026Observational
- Grounded report generation for enhancing ophthalmic ultrasound interpretation using Vision-Language Segmentation models.NPJ digital medicine · 2026Article
- Leveraging ChatGPT for Report Error Audit: An Accuracy-Driven and Cost-Efficient Solution for Ophthalmic Imaging Reports.Ophthalmology and therapy · 2025Article
- Generative artificial intelligence for fundus fluorescein angiography interpretation and human expert evaluation.NPJ digital medicine · 2025Article
- Integrating Artificial Intelligence and Precision Therapeutics for Advancing the Diagnosis and Treatment of Age-Related Macular Degeneration.Bioengineering (Basel, Switzerland) · 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
- Artificial intelligence for posterior capsule opacification.Frontiers in medicine · 2025Review
- Knowledge-enhanced AI drives diagnosis of multiple retinal diseases in fundus fluorescein angiography.Frontiers in cell and developmental biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fundus fluorescein angiography (FFA) serves as the current gold standard for visualizing retinal vasculature and detecting various fundus diseases, but its interpretation is labor-intensive and requires much expertise from ophthalmologists. The medical application of artificial intelligence (AI), especially deep learning and machine learning, has revolutionized the field of automatic FFA image analysis, leading to the rapid advancements in AI-assisted lesion detection, diagnosis, and report generation. This review examined studies in PubMed, Web of Science, and Google Scholar databases from January 2019 to August 2024, with a total of 23 articles incorporated. By integrating current research findings, this review highlights crucial breakthroughs in AI-assisted FFA analysis and explores their potential implications for ophthalmic clinical practice. These advances in AI-assisted FFA analysis have shown promising results in improving diagnostic accuracy and workflow efficiency. However, further research is needed to enhance model transparency and ensure robust performance across diverse populations. Challenges such as data privacy and technical infrastructure remain for broader clinical applications.
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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.