ArticleEye banking and corneal transplantation2026
Agentic Artificial Intelligence in Eye Banking: A Proposed Workflow.
Article in Eye banking and corneal transplantation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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Who cites it
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Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Purpose: To develop an agentic artificial intelligence (AI) framework that streamlines and standardizes eye bank operations by automating donor screening, image analysis, and tissue suitability assessment under expert supervision. Methods: A modular, on-premises, multi-agent system was designed consisting of three AI agents. The Donor Screening Agent analyzes medical histories to identify contraindications for ocular donation. The Corneal Image Analysis Agent interprets multimodal images, including specular microscopy, slit-lamp, and optical coherence tomography, to quantify endothelial cell density, morphology, and clarity. The Suitability Assessment Agent integrates outputs from both preceding agents to generate structured recommendations for transplantation, research use, or rejection. Each agent operates locally to ensure privacy, real-time processing, and compliance with health information regulations. Results: The proposed architecture replaces fragmented manual workflows with a unified, intelligent system that reduces variability, accelerates evaluations, and enhances transparency. By enabling consistent and rapid analysis of donor data and corneal images, the system can improve tissue utilization and decrease discard rates. A modular, low-latency design supports deployment in diverse settings, including low- and middle-income countries, where connectivity and infrastructure may be limited. Conclusions: Agentic AI offers a scalable pathway toward a standardized eye banking process by combining automation with human oversight. This approach has the potential to improve decision quality, operational efficiency, and equity in corneal transplantation. It carries implications for both limited resource settings and the broader context of transplantation medicine.
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Registered trials
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