ArticleCell reports. Medicine2023
An artificial intelligence system for the whole process from diagnosis to treatment suggestion of ischemic retinal diseases.
Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 20 citations in OpenAlex.
- The Underutilized Ocular Fundus in Emergency Departments: Current Progress and Future Prospect of Imaging and Artificial Intelligence for Patient Care.Ophthalmology science · 2026Review
- Review
- Intelligent Staging Performance of Diabetic Retinopathy Based on Fundus Fluorescein Angiography Images with Different Angiographic Phases.Bioengineering (Basel, Switzerland) · 2026Article
- Automated interpretation of fundus fluorescein angiography with multi-retinal vascular lesion segmentation.Frontiers in medicine · 2026Article
- Dual-database Bibliometric Analysis Combined with Gephi-based Network Visualization of Artificial Intelligence Applications in the Identification and Diagnosis of Thyroid Space-occupying Lesions.Current medical imaging · 2026Article
- Article
- Automated quantification of retinal non-perfusion areas in ultra-widefield SS-OCTA image of patient with retinal vascular diseases by NP-Unet model.BMJ open ophthalmology · 2025Article
- Review
- S2S: A deep learning method for the radiological diagnosis of fine-grained diseases spanning screening to subtyping.Patterns (New York, N.Y.) · 2025Article
- Establishment of a novel alloxan-induced rabbit model exhibiting unique diabetic retinal neuropathy features assessed via ERG + VEP.Animal models and experimental medicine · 2025Article
- RB-Care: An Artificial Intelligence System for Automatic Quantitative Assessment and Surveillance of Retinoblastoma.Translational vision science & technology · 2025Article
- Intergrader Agreement on Qualitative and Quantitative Assessment of Diabetic Retinopathy Severity Using Ultra-Widefield Imaging: INSPIRED Study Report 1.Diagnostics (Basel, Switzerland) · 2025Article
- A Systematic Review of Advances in AI-Assisted Analysis of Fundus Fluorescein Angiography (FFA) Images: From Detection to Report Generation.Ophthalmology and therapy · 2025Review
- Predictors of macular edema recurrence and visual outcomes in branch retinal vein occlusion treated with aflibercept or ranibizumab.International ophthalmology · 2025Article
- Artificial intelligence in cataract grading system: a LOCS III-based hybrid model achieving high-precision classification.Frontiers in cell and developmental biology · 2025Article
- Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- The application of artificial intelligence in diabetic retinopathy: progress and prospects.Frontiers in cell and developmental biology · 2024Review
- Multi-Layer Preprocessing and U-Net with Residual Attention Block for Retinal Blood Vessel Segmentation.Diagnostics (Basel, Switzerland) · 2023Article
- Deep learning for precision medicine: Guiding laser therapy in ischemic retinal diseases.Cell reports. Medicine · 2023Article
- Diabetic Retinopathy Assessment through Multitask Learning Approach on Heterogeneous Fundus Image Datasets.Ophthalmology scienceArticle
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ischemic retinal diseases (IRDs) are a series of common blinding diseases that depend on accurate fundus fluorescein angiography (FFA) image interpretation for diagnosis and treatment. An artificial intelligence system (Ai-Doctor) was developed to interpret FFA images. Ai-Doctor performed well in image phase identification (area under the curve [AUC], 0.991-0.999, range), diabetic retinopathy (DR) and branch retinal vein occlusion (BRVO) diagnosis (AUC, 0.979-0.992), and non-perfusion area segmentation (Dice similarity coefficient [DSC], 89.7%-90.1%) and quantification. The segmentation model was expanded to unencountered IRDs (central RVO and retinal vasculitis), with DSCs of 89.2% and 83.6%, respectively. A clinically applicable ischemia index (CAII) was proposed to evaluate ischemic degree; patients with CAII values exceeding 0.17 in BRVO and 0.08 in DR may be associated with increased possibility for laser therapy. Ai-Doctor is expected to achieve accurate FFA image interpretation for IRDs, potentially reducing the reliance on retinal specialists.
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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.