Cell Rep. Med. | 金凯团队构建自主多模态眼科智能体AgentEYE实现循证、可追溯的眼科诊断

TL;DR - AgentEYE is an autonomous multimodal ophthalmic AI agent from Kai Jin's team (Second Affiliated Hospital, Zhejiang University School of Medicine), published in Cell Reports Medicine (Aug 5, 2026), that routes fundus photos and ocular B-scan ultrasound to specialist tools, retrieves clinical guideline/web evidence, and emits auditable diagnostic reports with verifiable citations. It matters because it targets the weak-evidence, non-traceable failure modes that block clinical deployment of general LLMs on medical imaging.

• Modular agent pipeline: modality recognition/routing → specialist image analysis tools → evidence retrieval with sufficiency checking and query refinement → report integration (diagnosis, differentials, management, references), with inspectable intermediate states at each step.
• Built on 9,049 patients, 31,393 fundus images, 43,266 ocular ultrasound images, and 15,244 reference reports/PDFs; internal test on 302 same-day dual-modality cases scored 71.93 correctness / 75.59 completeness vs. 36.52 / 48.57 for a general LLM reading images directly.
• Blinded review by 3 ophthalmologists on 200 cases (1,200 ratings): 83.0% correct vs. 42.0% baseline, 82.5% complete vs. 41.5%, potentially harmful output 3.5% vs. 29.0%, and 86.5% correct citations vs. 46.5% — unverifiable/fabricated references appeared only in the baseline.
• Ablations show specialist imaging tools drive accuracy (removing them drops correctness to 39.40) while retrieval mainly adds evidence grounding and auditability; external validation (Wannan Medical College +18.53 correctness; smaller Polish cohort roughly at parity, no gain on unseen disease labels) bounds it as a physician-supervised decision-support tool, not open-world diagnosis. Code: github.com/OpenMedAILab/AgentEYE.